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Checcucci E, Piana A, Volpi G, Quarà A, De Cillis S, Piramide F, Burgio M, Meziere J, Cisero E, Colombo M, Bignante G, Sica M, Granato S, Verri P, Gatti C, Alessio P, Di Dio M, Alba S, Fiori C, Amparore D, Porpiglia F. Visual extended reality tools in image-guided surgery in urology: a systematic review. Eur J Nucl Med Mol Imaging 2024; 51:3109-3134. [PMID: 38589511 DOI: 10.1007/s00259-024-06699-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 03/19/2024] [Indexed: 04/10/2024]
Abstract
PURPOSE The aim of this systematic review is to assess the clinical implications of employing various Extended Reality (XR) tools for image guidance in urological surgery. METHODS In June 2023, a systematic electronic literature search was conducted using the Medline database (via PubMed), Embase (via Ovid), Scopus, and Web of Science. The search strategy was designed based on the PICO (Patients, Intervention, Comparison, Outcome) criteria. Study protocol was registered on PROSPERO (registry number CRD42023449025). We incorporated retrospective and prospective comparative studies, along with single-arm studies, which provided information on the use of XR, Mixed Reality (MR), Augmented Reality (AR), and Virtual Reality (VR) in urological surgical procedures. Studies that were not written in English, non-original investigations, and those involving experimental research on animals or cadavers were excluded from our analysis. The quality assessment of comparative and cohort studies was conducted utilizing the Newcastle-Ottawa scale, whilst for randomized controlled trials (RCTs), the Jadad scale was adopted. The level of evidence for each study was determined based on the guidelines provided by the Oxford Centre for Evidence-Based Medicine. RESULTS The initial electronic search yielded 1,803 papers after removing duplicates. Among these, 58 publications underwent a comprehensive review, leading to the inclusion of 40 studies that met the specified criteria for analysis. 11, 20 and 9 studies tested XR on prostate cancer, kidney cancer and miscellaneous, including bladder cancer and lithiasis surgeries, respectively. Focusing on the different technologies 20, 15 and 5 explored the potential of VR, AR and MR. The majority of the included studies (i.e., 22) were prospective non-randomized, whilst 7 and 11 were RCT and retrospective studies respectively. The included studies that revealed how these new tools can be useful both in preoperative and intraoperative setting for a tailored surgical approach. CONCLUSIONS AR, VR and MR techniques have emerged as highly effective new tools for image-guided surgery, especially for urologic oncology. Nevertheless, the complete clinical advantages of these innovations are still in the process of evaluation.
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Affiliation(s)
- Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Strada Provinciale 142, km 3,95, Candiolo, Turin, 10060, Italy.
| | - Alberto Piana
- Department of Urology, Romolo Hospital, Rocca di Neto, Italy
| | - Gabriele Volpi
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Strada Provinciale 142, km 3,95, Candiolo, Turin, 10060, Italy
| | - Alberto Quarà
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Sabrina De Cillis
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Federico Piramide
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Mariano Burgio
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Juliette Meziere
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Edoardo Cisero
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Marco Colombo
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Gabriele Bignante
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Michele Sica
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Stefano Granato
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Paolo Verri
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Cecilia Gatti
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Strada Provinciale 142, km 3,95, Candiolo, Turin, 10060, Italy
| | - Paolo Alessio
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Strada Provinciale 142, km 3,95, Candiolo, Turin, 10060, Italy
| | - Michele Di Dio
- Dept. of Surgery, Division of Urology, SS Annunziata Hospital, Cosenza, Italy
| | - Stefano Alba
- Department of Urology, Romolo Hospital, Rocca di Neto, Italy
| | - Cristian Fiori
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Daniele Amparore
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Francesco Porpiglia
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
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Liu Y, Jiang A, Li J, He Z, Luo P, Qu L, Wang L. Navigating the future of genitourinary cancer treatment: a decade of progress in image-guided surgery. Int J Surg 2024; 110:4506-4507. [PMID: 39042079 PMCID: PMC11254253 DOI: 10.1097/js9.0000000000001438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Accepted: 03/24/2024] [Indexed: 07/24/2024]
Affiliation(s)
- Ying Liu
- Department of Urology, Changhai Hospital, Naval Medical University, Shanghai
| | - Aimin Jiang
- Department of Urology, Changhai Hospital, Naval Medical University, Shanghai
| | - Jinxin Li
- Department of Urology, Changhai Hospital, Naval Medical University, Shanghai
| | - Ziwei He
- Department of Urology, Changhai Hospital, Naval Medical University, Shanghai
| | - Peng Luo
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou
| | - Le Qu
- Department of Urology, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, People’s Republic of China
| | - Linhui Wang
- Department of Urology, Changhai Hospital, Naval Medical University, Shanghai
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Okada A, Ohashi K, Hashimoto H, Ota Y, Sugino T, Unno R, Iwatsuki S, Etani T, Taguchi K, Naiki T, Kurokawa S, Hamamoto S, Ando R, Nakane A, Kawai N, Tozawa K, Yasui T. Three-dimensional computed tomography-based resection process map for robot-assisted partial nephrectomy: propensity score matching of a single-center retrospective study. J Surg Oncol 2024; 129:1311-1324. [PMID: 38470556 DOI: 10.1002/jso.27615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 01/22/2024] [Accepted: 02/11/2024] [Indexed: 03/14/2024]
Abstract
BACKGROUND AND OBJECTIVES We aimed to examine the effect of preoperative three-dimensional (3D) computed tomography (CT)-based resection process map (RPM) imaging on the outcomes of robot-assisted partial nephrectomy (RAPN). METHODS We retrospectively analyzed 177 patients (RPM group, n = 92; non-RPM group, n = 85) who underwent this surgery between November 2012 and April 2022. Patient-specific contrast-enhanced CT images were used to construct an RPM, a 3D representation of the kidney showing the planned tumor resection and a 5 mm safety margin. Outcome analyses were performed using propensity score matching. The primary endpoint was the trifecta achievement rate. RESULTS We extracted 90 cases. The trifecta achievement rate showed no significant differences between the RPM (73.3%) and non-RPM groups (73.3%). However, the RPM group had fewer Grade 3 and higher complications (0.0% vs. 13.3%, p = 0.026). The da Vinci Xi (OR 3.38, p = 0.016) and tumor diameter (OR 0.95, p = 0.013) were independent factors affecting trifecta achievement in multivariate analysis. Using RPM imaging was associated with the absence of Grade 3 and higher perioperative complications (OR 5.33, p = 0.036) in univariate analysis. CONCLUSIONS Using preoperative 3D CT-based RPM images before RAPN may not affect trifecta achievement, but may reduce serious complication occurrence by providing detailed information on tumor resection.
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Affiliation(s)
- Atsushi Okada
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Kazuya Ohashi
- Department of Radiology, Nagoya City University Hospital, Nagoya, Japan
- Department of Radiology, Nagoya City University Midori Municipal Hospital, Nagoya, Japan
| | - Hiroya Hashimoto
- Clinical Research Center, National Hospital Organization Nagoya Medical Center, Nagoya, Japan
| | - Yuya Ota
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Teruaki Sugino
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Rei Unno
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Shoichiro Iwatsuki
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Toshiki Etani
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Kazumi Taguchi
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Taku Naiki
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Satoshi Kurokawa
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Shuzo Hamamoto
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Ryosuke Ando
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Akihiro Nakane
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Noriyasu Kawai
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Keiichi Tozawa
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Takahiro Yasui
- Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
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Piana A, Pecoraro A, Dönmez Mİ, Prudhomme T, Bañuelos Marco B, López Abad A, Campi R, Boissier R, Checcucci E, Amparore D, Porpiglia F, Breda A, Territo A. New frontiers in kidney transplantation: Towards the extended reality. Actas Urol Esp 2024; 48:337-339. [PMID: 37981169 DOI: 10.1016/j.acuroe.2023.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 10/04/2023] [Indexed: 11/21/2023]
Affiliation(s)
- Alberto Piana
- Departmento de Urología, Universidad de Turín, Turín, Italy; Servicio de Urología, Hospital Romolo, Rocca di Neto, Italy.
| | - Alessio Pecoraro
- Departmento de Medicina Experimental y Clínica, Universidad de Florencia, Florencia, Italy
| | - Muhammet İrfan Dönmez
- Departmento de Urología, Facultad de Medicina de la Universidad de Estambul, Estambul, Turkey
| | - Thomas Prudhomme
- Servicio de Urología, Trasplante Renal y Andrología, Hospital Universitario de Rangueil, Toulouse, France
| | - Beatriz Bañuelos Marco
- Sección de Trasplante Renal y Urología Reconstructiva, Hospital Universitario Clínico San Carlos, Madrid, Spain
| | - Alicia López Abad
- Departmento de Medicina Experimental y Clínica, Universidad de Florencia, Florencia, Italy; Servicio de Urología, Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain
| | - Riccardo Campi
- Departmento de Medicina Experimental y Clínica, Universidad de Florencia, Florencia, Italy
| | - Romain Boissier
- Servicio de Urología y Trasplante Renal, Hospital Universitario La Conception, Marsella, France
| | - Enrico Checcucci
- Servicio de Cirugía, Instituto de Candiolo FPO-IRCCS, Candiolo, Turín, Italy
| | | | | | - Alberto Breda
- Unidad de Uro-oncología y Trasplante Renal, Servicio de Urología, Fundación Puigvert, Universidad Autónoma de Barcelona (UAB), Barcelona, Spain
| | - Angelo Territo
- Unidad de Uro-oncología y Trasplante Renal, Servicio de Urología, Fundación Puigvert, Universidad Autónoma de Barcelona (UAB), Barcelona, Spain
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van Leeuwen FWB, Buckle T, Rietbergen DDD, van Oosterom MN. The realization of medical devices for precision surgery - development and implementation of ' stop-and-go' imaging technologies. Expert Rev Med Devices 2024; 21:349-358. [PMID: 38722051 DOI: 10.1080/17434440.2024.2341102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 04/05/2024] [Indexed: 05/31/2024]
Abstract
INTRODUCTION Surgery and biomedical imaging encompass a big share of the medical-device market. The ever-mounting demand for precision surgery has driven the integration of these two into the field of image-guided surgery. A key-question herein is how imaging modalities can guide the surgical decision-making process. Through performance-based design, chemists, engineers, and doctors need to build a bridge between imaging technologies and surgical challenges. AREAS-COVERED This perspective article highlights the complementary nature between the technological design of an image-guidance modality and the type of procedure performed. The specific roles of the involved professionals, imaging technologies, and surgical indications are addressed. EXPERT-OPINION Molecular-image-guided surgery has the potential to advance pre-, intra- and post-operative tissue characterization. To achieve this, surgeons need the access to well-designed indication-specific chemical-agents and detection modalities. Hereby, some technologies stimulate exploration ('go'), while others stimulate caution ('stop'). However, failing to adequately address the indication-specific needs rises the risk of incorrect tool employment and sub-optimal surgical performance. Therefore, besides the availability of new technologies, market growth is highly dependent on the practical nature and impact on real-life clinical care. While urology currently takes the lead in the widespread implementation of image-guidance technologies, the topic is generic and its popularity spreads rapidly within surgical oncology.
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Affiliation(s)
- Fijs W B van Leeuwen
- Interventional Molecular Imaging Laboratory, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Tessa Buckle
- Interventional Molecular Imaging Laboratory, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Daphne D D Rietbergen
- Interventional Molecular Imaging Laboratory, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Matthias N van Oosterom
- Interventional Molecular Imaging Laboratory, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
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Mihai I, Dura H, Teodoru CA, Todor SB, Ichim C, Grigore N, Mohor CI, Mihetiu A, Oprinca G, Bacalbasa N, Tanasescu D, Bratu DG, Boicean A, Oros B, Hasegan A. Intraoperative Ultrasound: Bridging the Gap between Laparoscopy and Surgical Precision during 3D Laparoscopic Partial Nephrectomies. Diagnostics (Basel) 2024; 14:942. [PMID: 38732356 PMCID: PMC11083918 DOI: 10.3390/diagnostics14090942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 04/11/2024] [Accepted: 04/25/2024] [Indexed: 05/13/2024] Open
Abstract
The use of 3D laparoscopic partial nephrectomy has emerged as a cornerstone in the surgical arsenal for addressing renal tumors, particularly in managing challenging cases characterized by deeply seated tumors embedded within the renal parenchyma. In these intricate scenarios, the utilization of intraoperative ultrasound (IOUS) acquires paramount importance, serving as an indispensable tool for guiding and meticulously monitoring the surgical process in real time. To further explore the efficacy of IOUS-guided techniques, we conducted a retrospective study comparing outcomes in patients who underwent partial nephrectomy with IOUS guidance (n = 60) between 2020 and 2022 with a cohort from 2018 to 2019 without IOUS guidance (n = 25). Our comprehensive analysis encompassed various post-operative parameters, including the duration until food resumption, analgesia requirements, and length of the hospital stay. While these parameters exhibited comparable outcomes between the two groups, notable distinctions emerged in the intraoperative metrics. The IOUS-guided cohort demonstrated significantly reduced blood loss, a shorter median operative duration, and diminished ischemia time (p = 0.001). These compelling findings underscore the undeniable benefits of IOUS-guided techniques in not only facilitating the attainment of negative surgical margins but also in enhancing procedural safety and precision, thereby contributing to improved patient outcomes in the management of renal tumors.
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Affiliation(s)
- Ionela Mihai
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
| | - Horatiu Dura
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
| | - Cosmin Adrian Teodoru
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
| | - Samuel Bogdan Todor
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
| | - Cristian Ichim
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
| | - Nicolae Grigore
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
| | - Cosmin Ioan Mohor
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
| | - Alin Mihetiu
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
| | - George Oprinca
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
| | - Nicolae Bacalbasa
- Surgery Department, University of Medicine and Pharmacy “Carol Davila” Bucharest, 020021 Bucharest, Romania;
| | - Denisa Tanasescu
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
| | - Dan Georgian Bratu
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
| | - Adrian Boicean
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
| | - Bogdan Oros
- County Clinical Emergency Hospital of Sibiu, 550245 Sibiu, Romania
| | - Adrian Hasegan
- Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania; (I.M.); (C.A.T.); (S.B.T.); (C.I.); (N.G.); (C.I.M.); (A.M.); (G.O.); (D.T.); (D.G.B.); (A.B.); (A.H.)
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Cannon PC, Setia SA, Klein-Gardner S, Kavoussi NL, Webster RJ, Herrell SD. Are 3D Image Guidance Systems Ready for Use? A Comparative Analysis of 3D Image Guidance Implementations in Minimally Invasive Partial Nephrectomy. J Endourol 2024; 38:395-407. [PMID: 38251637 PMCID: PMC10979686 DOI: 10.1089/end.2023.0059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2024] Open
Abstract
Introduction: Three-dimensional image-guided surgical (3D-IGS) systems for minimally invasive partial nephrectomy (MIPN) can potentially improve the efficiency and accuracy of intraoperative anatomical localization and tumor resection. This review seeks to analyze the current state of research regarding 3D-IGS, including the evaluation of clinical outcomes, system functionality, and qualitative insights regarding 3D-IGS's impact on surgical procedures. Methods: We have systematically reviewed the clinical literature pertaining to 3D-IGS deployed for MIPN. For inclusion, studies must produce a patient-specific 3D anatomical model from two-dimensional imaging. Data extracted from the studies include clinical results, registration (alignment of the 3D model to the surgical scene) method used, limitations, and data types reported. A subset of studies was qualitatively analyzed through an inductive coding approach to identify major themes and subthemes across the studies. Results: Twenty-five studies were included in the review. Eight (32%) studies reported clinical results that point to 3D-IGS improving multiple surgical outcomes. Manual registration was the most utilized (48%). Soft tissue deformation was the most cited limitation among the included studies. Many studies reported qualitative statements regarding surgeon accuracy improvement, but quantitative surgeon accuracy data were not reported. During the qualitative analysis, six major themes emerged across the nine applicable studies. They are as follows: 3D-IGS is necessary, 3D-IGS improved surgical outcomes, researcher/surgeon confidence in 3D-IGS system, enhanced surgeon ability/accuracy, anatomical explanation for qualitative assessment, and claims without data or reference to support. Conclusions: Currently, clinical outcomes are the main source of quantitative data available to point to 3D-IGS's efficacy. However, the literature qualitatively suggests the benefit of accurate 3D-IGS for robotic partial nephrectomy.
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Affiliation(s)
- Piper C. Cannon
- Department of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Shaan A. Setia
- Department of Urologic Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Stacy Klein-Gardner
- Department of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Nicholas L. Kavoussi
- Department of Urologic Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Robert J. Webster
- Department of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - S. Duke Herrell
- Department of Urologic Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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Amparore D, Checcucci E, Piramide F, Busacca G, Volpi G, De Cillis S, Sica M, Verri P, Piana A, Di Dio M, Fiori C, Porpiglia F. Robotic Vena Cava Thrombectomy with Three-dimensional Augmented Reality Guidance. EUR UROL SUPPL 2024; 62:43-46. [PMID: 38434189 PMCID: PMC10909593 DOI: 10.1016/j.euros.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/02/2024] [Indexed: 03/05/2024] Open
Abstract
Robotic surgery has recently been used for treatment of renal cell carcinoma (RCC) and neoplastic thrombus located in the renal vein or inferior vena cava (IVC). Accurate identification of the thrombus location is crucial, and three-dimensional augmented reality (3D AR) may be valuable in achieving this. We enrolled patients with nonmetastatic RCC and level 0-I venous thrombus (Mayo Clinic classification) for robot-assisted radical nephrectomy and thrombectomy with 3D AR guidance. Five patients were prospectively enrolled; three had a level 0 thrombus and two had a level I thrombus. The mean operative time was 123 ± 15 min, mean IVC clamping time was 9.4 ± 6.8 min, and mean estimated blood loss was 750 ± 150 ml. The AR system allowed precise estimation of the thrombus location in all cases. No intraoperative complications or postoperative Clavien-Dindo grade >2 complications occurred. Use of 3D AR guidance allowed correct estimation of the limits of the thrombus and guided the surgeon in selecting an appropriate surgical strategy.
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Affiliation(s)
- Daniele Amparore
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy
| | - Federico Piramide
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Giovanni Busacca
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Gabriele Volpi
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy
| | - Sabrina De Cillis
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Michele Sica
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Paolo Verri
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | | | - Michele Di Dio
- Division of Urology, Department of Surgery, SS Annunziata Hospital, Cosenza, Italy
| | - Cristian Fiori
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Francesco Porpiglia
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
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9
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Piana A, Amparore D, Sica M, Volpi G, Checcucci E, Piramide F, De Cillis S, Busacca G, Scarpelli G, Sidoti F, Alba S, Piazzolla P, Fiori C, Porpiglia F, Di Dio M. Automatic 3D Augmented-Reality Robot-Assisted Partial Nephrectomy Using Machine Learning: Our Pioneer Experience. Cancers (Basel) 2024; 16:1047. [PMID: 38473404 DOI: 10.3390/cancers16051047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 02/26/2024] [Accepted: 02/29/2024] [Indexed: 03/14/2024] Open
Abstract
The aim of "Precision Surgery" is to reduce the impact of surgeries on patients' global health. In this context, over the last years, the use of three-dimensional virtual models (3DVMs) of organs has allowed for intraoperative guidance, showing hidden anatomical targets, thus limiting healthy-tissue dissections and subsequent damage during an operation. In order to provide an automatic 3DVM overlapping in the surgical field, we developed and tested a new software, called "ikidney", based on convolutional neural networks (CNNs). From January 2022 to April 2023, patients affected by organ-confined renal masses amenable to RAPN were enrolled. A bioengineer, a software developer, and a surgeon collaborated to create hyper-accurate 3D models for automatic 3D AR-guided RAPN, using CNNs. For each patient, demographic and clinical data were collected. A total of 13 patients were included in the present study. The average anchoring time was 11 (6-13) s. Unintended 3D-model automatic co-registration temporary failures happened in a static setting in one patient, while this happened in one patient in a dynamic setting. There was one failure; in this single case, an ultrasound drop-in probe was used to detect the neoplasm, and the surgery was performed under ultrasound guidance instead of AR guidance. No major intraoperative nor postoperative complications (i.e., Clavien Dindo > 2) were recorded. The employment of AI has unveiled several new scenarios in clinical practice, thanks to its ability to perform specific tasks autonomously. We employed CNNs for an automatic 3DVM overlapping during RAPN, thus improving the accuracy of the superimposition process.
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Affiliation(s)
- Alberto Piana
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Daniele Amparore
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Michele Sica
- Department of Surgery, Candiolo Cancer Institute FPO-IRCCS, 10060 Turin, Italy
| | - Gabriele Volpi
- Department of Surgery, Candiolo Cancer Institute FPO-IRCCS, 10060 Turin, Italy
| | - Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute FPO-IRCCS, 10060 Turin, Italy
| | - Federico Piramide
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Sabrina De Cillis
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Giovanni Busacca
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | | | | | | | - Pietro Piazzolla
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Cristian Fiori
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Francesco Porpiglia
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Michele Di Dio
- Division of Urology, Department of Surgery, Annunziata Hospital, 87100 Cosenza, Italy
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10
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Liu W, Zhang E, Zhang M. Current Application of Navigation Systems in Robotic-Assisted and Laparoscopic Partial Nephrectomy: Focus on the Improvement of Surgical Performance and Outcomes. Ann Surg Oncol 2024; 31:2163-2172. [PMID: 38063985 DOI: 10.1245/s10434-023-14716-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 11/20/2023] [Indexed: 01/09/2024]
Abstract
Kidney cancer represents the third most prevalent malignancy among all types of genitourinary cancer worldwide. Currently, there is a growing trend of employing partial nephrectomy for the management of large and complex tumors. Surgical outcomes are associated with some amendable surgical factors, including warm ischemic time, pedicle clamping, preserved volume of renal parenchyma, appropriate surgical strategy, and precise resection of the tumor. Improving surgical performance is pivotal for achieving favorable surgical outcomes. Due to advancements in imaging visualization technology and the shift of the medical paradigm toward precision medicine, an increasing number of navigation systems have been implemented in partial nephrectomy procedures. The navigation system can assist surgeons in formulating optimal surgical strategies and enhance the safety, precision, and feasibility of resecting complex renal tumors. In this review, we provide an overview of currently available navigation systems and their feasible applications, with a focus on how they contribute to the improvement of surgical performance and outcomes during robotic-assisted and laparoscopic partial nephrectomy.
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Affiliation(s)
- Wangmin Liu
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Enchong Zhang
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China.
| | - Mo Zhang
- Department of Urology, The First Hospital of China Medical University, Shenyang, China.
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11
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Volpe A, Capitanio U, Falsaperla M, Giannarini G, Palumbo C, Antonelli A, Minervini A, Ficarra V. Partial nephrectomy for renal tumors: recommendations of the Italian Society of Urology RCC working group. Minerva Urol Nephrol 2024; 76:9-21. [PMID: 38426419 DOI: 10.23736/s2724-6051.24.05772-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Abstract
INTRODUCTION Partial nephrectomy (PN) aims to remove renal tumors while preserving renal function without affecting oncological and perioperative surgical outcomes. Aim of this paper is to summarize the current evidence on PN and to provide evidence-based recommendations on indications, surgical technique, perioperative management and postoperative surveillance of PN for renal tumors in the Italian clinical and health care system context. EVIDENCE ACQUISITION This review is the result of an interactive peer-reviewing process of the recent literature on PN for renal tumors carried out by an expert panel composed of members of the Italian Society of Urology (SIU) Renal Cell Carcinoma Working Group. EVIDENCE SYNTHESIS PN for localized renal tumors is not inferior to radical nephrectomy in terms of survival outcomes while significantly better preserving renal function. Loss of renal function after PN is influenced by medical comorbidities/preoperative renal function and surgical variables such volume of parenchyma preserved and ischemia time. Urologists should select the clamping strategy during PN based on their experience and patient-specific factors. PN can be performed with any surgical approach based on surgeon's expertise and skills. Robotic PN has the potential to expand the minimally invasive indications without interfering with oncological outcomes. The use of 3D virtual models, real time ultrasound and fluorescence tools to assess the anatomy and vascularization of renal tumors during PN may allow a more accurate preoperative planning and intraoperative guidance. Proper postoperative surveillance protocols are essential to detect tumor recurrences and assess functional outcomes. CONCLUSIONS PN is the standard of care for treatment of localized T1 renal tumors. Recent data supports PN also for selected T2-T3a tumors in experienced institutions. Careful preoperative planning, adequate surgical skills and volumes and appropriate postoperative management and surveillance are paramount to optimize PN oncological and functional outcomes.
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Affiliation(s)
- Alessandro Volpe
- Division of Urology, Department of Translational Medicine, Maggiore della Carità Hospital, University of Eastern Piedmont, Novara, Italy -
| | - Umberto Capitanio
- Unit of Urology, Division of Experimental Oncology, Urological Research Institute (URI), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Mario Falsaperla
- Unit of Urology, Presidio Ospedaliero Vittorio Emanuele, Vittorio Emanuele Polyclinic University Hospital, Catania, Italy
| | - Gianluca Giannarini
- Unit of Urology, Santa Maria della Misericordia University Hospital, Udine, Italy
| | - Carlotta Palumbo
- Division of Urology, Department of Translational Medicine, Maggiore della Carità Hospital, University of Eastern Piedmont, Novara, Italy
| | - Alessandro Antonelli
- Department of Urology, University of Verona, Azienda Ospedaliera Universitaria Integrata di Verona, Verona, Italy
| | - Andrea Minervini
- Unit of Oncologic Minimally-Invasive Urology and Andrology, Department of Experimental and Clinical Medicine, Careggi Hospital, University of Florence, Florence, Italy
| | - Vincenzo Ficarra
- Unit of Urology, Department of Oncology, G. Martino Polyclinic Hospital, Messina, Italy
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12
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Theivendrampillai S, Yang B, Little M, Blick C. Targeted augmented reality-guided transperineal prostate biopsies study: initial experience. Ther Adv Urol 2024; 16:17562872241232582. [PMID: 38464882 PMCID: PMC10924555 DOI: 10.1177/17562872241232582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 01/24/2024] [Indexed: 03/12/2024] Open
Abstract
Background Transperineal biopsy of magnetic resonance imaging (MRI)-detected prostate lesions is now the established technique used in prostate cancer (CaP) diagnostics. Virtual Surgery Intelligence (VSI) Holomedicine by Apoqlar (Hamburg, Germany) is a mixed reality (MR)/augmented reality (AR) software platform that runs on the HoloLens II system (Microsoft, Redford, USA). Multiparametric prostate MRI images were converted into 3D holograms and added into a MR space, enabling visualization of a 3D hologram and image-assisted prostate biopsy. Objective The Targeted Augmented Reality-GuidEd Transperineal (TARGET) study investigated the feasibility of performing AR-guided prostate biopsies in a MR framework, using the VSI platform in patients with MRI-detected prostate lesions. Methods Ten patients with a clinical suspicion of CaP on MRI (Prostate Imaging-Reporting and Data System, PI-RADS 4/5) were uploaded to the VSI HoloLens system. Two MR/AR-guided prostate biopsies were then acquired using the PrecisionPoint Freehand transperineal biopsy system. Cognitive fusion biopsies were performed as standard of care following the MR/AR-guided prostate biopsies. Results All 10 patients successfully underwent MR/AR-guided prostate biopsy after 3D MR images were overlaid on the patient's body. Prostatic tissue was obtained in all MR/AR-guided specimens. Seven patients (70%) had matching histology in both the standard and MR/AR-guided biopsies. The remaining three had ISUP (International Society of Urological Pathology) Grade 2 CaP. There were no immediate complications. Conclusion We believe this is a world first. The initial feasibility data from the TARGET study demonstrated that an MR/AR-guided prostate biopsy utilizing the VSI Holomedicine system is a viable option in CaP diagnostics. The next stage in development is to combine AR images with real-time needle insertion and to provide further data to formally appraise the sensitivity and specificity of the technique.
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Affiliation(s)
| | - Bob Yang
- Royal Berkshire Hospital, Reading, Berkshire, UK
| | - Mark Little
- Royal Berkshire Hospital, Reading, Berkshire, UK
| | - Christopher Blick
- Department of Urology, Royal Berkshire Hospital, Craven Road, Reading, Berkshire RG1 5AN, UK
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13
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Wu X, Zhou J, Chen W, Cai W, Liu D, Huang Y, Tricard T, Chen Y, Xue W. Retroperitoneoscopic Clampless, Sutureless Hybrid Therapy in the Management of Renal Hilar Tumors. Ann Surg Oncol 2024; 31:681-687. [PMID: 37903952 DOI: 10.1245/s10434-023-14248-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 08/14/2023] [Indexed: 11/01/2023]
Abstract
OBJECTIVE We aimed to investigate the outcomes and feasibility of a retroperitoneoscopic clampless, sutureless hybrid technique in the management of renal hilar tumors. METHODS A retrospective cohort of consecutive patients with renal hilar tumors who received retroperitoneoscopic clampless, sutureless hybrid therapy between January 2017 and April 2021 was included. The hybrid surgical technique involved microwave ablation (MWA), followed by clampless tumor enucleation and sutureless hemostasis. Surgical, pathological, and oncological outcomes were recorded and analyzed. RESULTS Sixty patients were included in this study. The median tumor size was 3.5 cm (2-5), the median RENAL score was 7 (range 6-10), the median operative time was 110 min (70-130), and the median estimated blood loss was 80 mL (30-130). The median length of postoperative hospital stay was 3 days (2-4), and no warm ischemia time was observed, except in one patient who required conversion to conventional on-clamp laparoscopic partial nephrectomy (LPN) with a 10 min warm ischemia time. Three minor complications (Clavien-Dindo grade I) and one major complication (Clavien-Dindo grade III) were recorded postoperatively. Thus far, no blood transfusions have been required. Renal dysfunction or tumor recurrence did not occur within a median follow-up of 45 months. CONCLUSION The retroperitoneoscopic hybrid technique involving MWA, clampless tumor enucleation, and sutureless hemostasis is a feasible and safe option for the management of selective renal hilar tumors. Complete tumor removal with maximal renal function preservation can be achieved, with a low complication rate.
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Affiliation(s)
- Xiaorong Wu
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Jiale Zhou
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Wei Chen
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Wei Cai
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Dongming Liu
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Yiran Huang
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Thibault Tricard
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
- Department of Urology, Nouvel Hôpital Civil, Hôpitaux Universitaire de Strasbourg, Strasbourg, France.
| | - Yonghui Chen
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
| | - Wei Xue
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
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14
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Amparore D, Sica M, Verri P, Piramide F, Checcucci E, De Cillis S, Piana A, Campobasso D, Burgio M, Cisero E, Busacca G, Di Dio M, Piazzolla P, Fiori C, Porpiglia F. Computer Vision and Machine-Learning Techniques for Automatic 3D Virtual Images Overlapping During Augmented Reality Guided Robotic Partial Nephrectomy. Technol Cancer Res Treat 2024; 23:15330338241229368. [PMID: 38374643 PMCID: PMC10878218 DOI: 10.1177/15330338241229368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024] Open
Abstract
OBJECTIVES The research's purpose is to develop a software that automatically integrates and overlay 3D virtual models of kidneys harboring renal masses into the Da Vinci robotic console, assisting surgeon during the intervention. INTRODUCTION Precision medicine, especially in the field of minimally-invasive partial nephrectomy, aims to use 3D virtual models as a guidance for augmented reality robotic procedures. However, the co-registration process of the virtual images over the real operative field is performed manually. METHODS In this prospective study, two strategies for the automatic overlapping of the model over the real kidney were explored: the computer vision technology, leveraging the super-enhancement of the kidney allowed by the intraoperative injection of Indocyanine green for superimposition and the convolutional neural network technology, based on the processing of live images from the endoscope, after a training of the software on frames from prerecorded videos of the same surgery. The work-team, comprising a bioengineer, a software-developer and a surgeon, collaborated to create hyper-accuracy 3D models for automatic 3D-AR-guided RAPN. For each patient, demographic and clinical data were collected. RESULTS Two groups (group A for the first technology with 12 patients and group B for the second technology with 8 patients) were defined. They showed comparable preoperative and post-operative characteristics. Concerning the first technology the average co-registration time was 7 (3-11) seconds while in the case of the second technology 11 (6-13) seconds. No major intraoperative or postoperative complications were recorded. There were no differences in terms of functional outcomes between the groups at every time-point considered. CONCLUSION The first technology allowed a successful anchoring of the 3D model to the kidney, despite minimal manual refinements. The second technology improved kidney automatic detection without relying on indocyanine injection, resulting in better organ boundaries identification during tests. Further studies are needed to confirm this preliminary evidence.
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Affiliation(s)
- Daniele Amparore
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Michele Sica
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Paolo Verri
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Federico Piramide
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute FPO-IRCCS, Candiolo, Italy
| | - Sabrina De Cillis
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Alberto Piana
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
- Department of Urology, Romolo Hospital, Rocca di Neto (KR), Italy
| | - Davide Campobasso
- Urology Unit, University Hospital of Parma, Parma, Italy
- 2 Level Master Degree Program in Advanced Robotic and Laparoscopic Surgery in Urology, Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi, Italy
| | - Mariano Burgio
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Edoardo Cisero
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Giovanni Busacca
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Michele Di Dio
- Division of Urology, Department of Surgery, Annunziata Hospital, Cosenza, Italy
| | - Pietro Piazzolla
- Department of Management and Production Engineer, Polytechnic University of Turin, Turin, Italy
| | - Cristian Fiori
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Francesco Porpiglia
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
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15
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La Barbera G, Rouet L, Boussaid H, Lubet A, Kassir R, Sarnacki S, Gori P, Bloch I. Tubular structures segmentation of pediatric abdominal-visceral ceCT images with renal tumors: Assessment, comparison and improvement. Med Image Anal 2023; 90:102986. [PMID: 37820418 DOI: 10.1016/j.media.2023.102986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 08/23/2023] [Accepted: 09/28/2023] [Indexed: 10/13/2023]
Abstract
Renal tubular structures, such as ureters, arteries and veins, are very important for building a complete digital 3D anatomical model of a patient. However, they can be challenging to segment from ceCT images due to their elongated shape, diameter variation and intra- and inter-patient contrast heterogeneity. This task is even more difficult in pediatric and pathological subjects, due to high inter-subject anatomical variations, potential presence of tumors, small volume of these structures compared to the surrounding, and small available labeled datasets. Given the limited literature on methods dedicated to children, and in order to find inspirational approaches, a complete assessment of state-of-the-art methods for the segmentation of renal tubular structures on ceCT images on adults is presented. Then, these methods are tested and compared on a private pediatric and pathological dataset of 79 abdominal-visceral ceCT images with arteriovenous phase acquisitions. To the best of our knowledge, both assessment and comparison in this specific case are novel. Eventually, we also propose a new loss function which leverages for the first time the use of vesselness functions on the predicted segmentation. We show that the combination of this loss function with state-of-the-art methods improves the topological coherence of the segmented tubular structures.2.
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Affiliation(s)
- Giammarco La Barbera
- LTCI, Télécom Paris, Institut Polytechnique de Paris, France; IMAG2, Institut Imagine, Université Paris Cité, France.
| | | | - Haithem Boussaid
- Philips Research Paris, Suresnes, France; Technology Innovation Institute, Abu Dhabi, United Arab Emirates
| | - Alexis Lubet
- IMAG2, Institut Imagine, Université Paris Cité, France
| | - Rani Kassir
- IMAG2, Institut Imagine, Université Paris Cité, France; Université Paris Cité, Department of Pediatric Surgery, Hôpital Necker Enfants-Malades, APHP, France
| | - Sabine Sarnacki
- IMAG2, Institut Imagine, Université Paris Cité, France; Université Paris Cité, Department of Pediatric Surgery, Hôpital Necker Enfants-Malades, APHP, France
| | - Pietro Gori
- LTCI, Télécom Paris, Institut Polytechnique de Paris, France
| | - Isabelle Bloch
- LTCI, Télécom Paris, Institut Polytechnique de Paris, France; IMAG2, Institut Imagine, Université Paris Cité, France; Sorbonne Université, CNRS, LIP6, Paris, France
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16
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Sica M, Piazzolla P, Amparore D, Verri P, De Cillis S, Piramide F, Volpi G, Piana A, Di Dio M, Alba S, Gatti C, Burgio M, Busacca G, Giordano A, Fiori C, Porpiglia F, Checcucci E. 3D Model Artificial Intelligence-Guided Automatic Augmented Reality Images during Robotic Partial Nephrectomy. Diagnostics (Basel) 2023; 13:3454. [PMID: 37998590 PMCID: PMC10670293 DOI: 10.3390/diagnostics13223454] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 11/03/2023] [Indexed: 11/25/2023] Open
Abstract
More than ever, precision surgery is making its way into modern surgery for functional organ preservation. This is possible mainly due to the increasing number of technologies available, including 3D models, virtual reality, augmented reality, and artificial intelligence. Intraoperative surgical navigation represents an interesting application of these technologies, allowing to understand in detail the surgical anatomy, planning a patient-tailored approach. Automatic superimposition comes into this context to optimally perform surgery as accurately as possible. Through a dedicated software (the first version) called iKidney, it is possible to superimpose the images using 3D models and live endoscopic images during partial nephrectomy, targeting the renal mass only. The patient is 31 years old with a 28 mm totally endophytic right-sided renal mass, with a PADUA score of 9. Thanks to the automatic superimposition and selective clamping, an enucleoresection of the renal mass alone was performed with no major postoperative complication (i.e., Clavien-Dindo < 2). iKidney-guided partial nephrectomy is safe, feasible, and yields excellent results in terms of organ preservation and functional outcomes. Further validation studies are needed to improve the prototype software, particularly to improve the rotational axes and avoid human help. Furthermore, it is important to reduce the costs associated with these technologies to increase its use in smaller hospitals.
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Affiliation(s)
- Michele Sica
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Pietro Piazzolla
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy; (P.P.); (G.V.); (C.G.)
| | - Daniele Amparore
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Paolo Verri
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Sabrina De Cillis
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Federico Piramide
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Gabriele Volpi
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy; (P.P.); (G.V.); (C.G.)
| | - Alberto Piana
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Michele Di Dio
- Division of Urology, Department of Surgery, SS Annunziata Hospital, 87100 Cosenza, Italy;
| | | | - Cecilia Gatti
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy; (P.P.); (G.V.); (C.G.)
| | - Mariano Burgio
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Giovanni Busacca
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Angelo Giordano
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Cristian Fiori
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Francesco Porpiglia
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Enrico Checcucci
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy; (P.P.); (G.V.); (C.G.)
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17
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Wei L, Wang C, Fu J, Qiangba T, Zhou X, He P, Li X, Lang L, Li C, Wang Y. Holographic 3D renal segments reconstruction protects renal function by promote choice of selective renal artery clamping during robot-assisted partial nephrectomy. World J Urol 2023; 41:2975-2983. [PMID: 37698633 DOI: 10.1007/s00345-023-04599-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 08/28/2023] [Indexed: 09/13/2023] Open
Abstract
OBJECTIVE To investigate the impact of selective artery clamping (SAC) and main artery clamping (MAC) during robot-assisted partial nephrectomy (RAPN) on renal function and the influence of holographic three-dimensional (3D) reconstruction of renal segments on the selection between SAC and MAC. METHODS This retrospective observational study included patients who underwent RAPN at First Hospital Affiliated to the Army Medical University between December 2016 and July 2022. According to the clamping methods, the patients were divided into the SAC group and the MAC group. The primary outcome was renal function. RESULTS A total of 422 patients (194 in the SAC group and 228 in the MAC group) were included. The RAPN procedures were all completed successfully. The patients in SAC group had less glomerular filtration rate (GFR) decline in the affected kidney (8.6 ± 7.0 ml/min vs. 18.7 ± 10.9 ml/min, P < 0.001) and minor estimated glomerular filtration rate (eGFR) decrease (4.3 ± 10.5 ml/min vs. 12.6 ± 12.1 ml/min, P < 0.001) than those in MAC group. Among 37 patients with baseline renal insufficiency, the GFR decline of the affected kidney in the SAC subgroup was significantly lower than in the MAC subgroup (5.5 ± 6.5 ml/min vs. 14.3 ± 9.2 ml/min, P = 0.002). The proportion of patients who underwent 3D reconstruction was significant higher in the SAC group than in the MAC group. (65.46% vs. 28.07%, P < 0.001). CONCLUSION The SAC technique during RAPN may serve as a protective measure for renal function, while the implementation of holographic 3D renal segment reconstruction technique may facilitate optimal selection of SAC.
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Affiliation(s)
- Ling Wei
- Department of Urology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China
| | - Cong Wang
- Department of Urology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China
| | - Jian Fu
- Department of Urology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China
| | - Tudan Qiangba
- Department of Urology, Tibet CORPS Hospital of Chinese People's Armed Police Forces, Lhasa, 850000, Tibet, China
| | - Xiaozhou Zhou
- Department of Urology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China
| | - Peng He
- Department of Urology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China
| | - Xuemei Li
- Department of Urology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China
| | - Lang Lang
- Department of Urology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China
| | - Chunxia Li
- Department of Urology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China
| | - Yongquan Wang
- Department of Urology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China.
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18
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Amparore D, Piramide F, Checcucci E, Verri P, De Cillis S, Piana A, Volpi G, Busacca G, Colombo M, Fiori C, Porpiglia F. Three-dimensional Virtual Models of the Kidney with Colored Perfusion Regions: A New Algorithm-based Tool for Optimizing the Clamping Strategy During Robot-assisted Partial Nephrectomy. Eur Urol 2023; 84:418-425. [PMID: 37117108 DOI: 10.1016/j.eururo.2023.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 03/25/2023] [Accepted: 04/04/2023] [Indexed: 04/30/2023]
Abstract
BACKGROUND An empirical selective clamping strategy based on the direction of the arterial branches can lead to failures during partial nephrectomy, even when assisted by three-dimensional virtual models (3DVMs). OBJECTIVE To develop and test new 3DVMs that include kidney perfusion regions and evaluate their intraoperative accuracy in guiding selective clamping and their impact on postoperative renal function. DESIGN, SETTING, AND PARTICIPANTS For patients with a kidney suitable for nephron-sparing surgery, 3DVMs were supplemented with a Voronoi diagram, a Euclidean distance-based mathematical tool, to calculate vascular-dominant regions the kidney. SURGICAL PROCEDURE Robot-assisted partial nephrectomy guided by perfusion-region (PR)-3DVMs. MEASUREMENTS All anatomic information given by the PR-3DVMs was collected. Selective or superselective clamping was planned and performed intraoperatively when feasible under 3DVM assistance. Changes in split renal function (SRF) and estimated renal plasmatic flow (ERPF) were evaluated for 51 patients who underwent baseline and 3-mo postoperative renal scintigraphy. RESULTS AND LIMITATIONS A total of 103 patients were prospectively enrolled. The median number of kidney and tumor perfusion regions were 8 (interquartile range [IQR] 7-10) and 3 (IQR 2-3), respectively. A clampless, selective clamping, and global clamping strategy was applied in eight (7.8%), 79 (76.6%), and 16 (15.5%) cases, respectively, with no differences between planning and surgery in terms of the number or order of arteries clamped or the perfusion regions that underwent ischemia. Among the 51 patients who underwent renal scintigraphy, the mean SRF decreased by 11.3%, 7.7%, and 1.7% after global, selective, and superselective clamping, respectively (p = 0.004). Similar results were obtained for ERPF (18.9%, 9.9%, and 6.0%; p = 0.02). The main limitation is the need for a bioengineer to manually refine the 3DVMs. CONCLUSIONS Use of mathematical algorithms for 3DVMs allows precise estimation of kidney perfusion regions to maximize the efficacy of selective clamping and minimize renal function impairment. PATIENT SUMMARY Three-dimensional models that include regions of blood flow to the kidney can be used to guide clamping of blood vessels when part of the kidney is being surgically removed. More limited clamping can reduce damage to the remaining portion of the kidney and result in better recovery of kidney function after surgery.
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Affiliation(s)
- Daniele Amparore
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Italy.
| | - Federico Piramide
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Italy
| | - Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute FPO-IRCCS, Candiolo, Italy
| | - Paolo Verri
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Italy
| | - Sabrina De Cillis
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Italy
| | - Alberto Piana
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Italy
| | - Gabriele Volpi
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Italy
| | - Giovanni Busacca
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Italy
| | - Marco Colombo
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Italy
| | - Cristian Fiori
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Italy
| | - Francesco Porpiglia
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Italy
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19
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Cerrato C, Meagher MF, Autorino R, Simone G, Yang B, Uzzo RG, Kutikov A, Porpiglia F, Capitanio U, Montorsi F, Porter J, Beksac AT, Puri D, Nguyen M, Wang L, Hakimi K, Dhanji S, Liu F, Cerruto MA, Pandolfo SD, Minervini A, Lau C, Monish A, Eun D, Mottrie A, Mir C, Sundaram C, Antonelli A, Kaouk J, Derweesh IH. Partial versus radical nephrectomy for complex renal mass: multicenter comparative analysis of functional outcomes (Rosula collaborative group). Minerva Urol Nephrol 2023; 75:425-433. [PMID: 37530659 DOI: 10.23736/s2724-6051.23.05123-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/03/2023]
Abstract
BACKGROUND Utility of partial nephrectomy (PN) for complex renal mass (CRM) is controversial. We determined the impact of surgical modality on postoperative renal functional outcomes for CRM. METHODS We retrospectively analyzed a multicenter registry (ROSULA). CRM was defined as RENAL Score 10-12. The cohort was divided into PN and radical nephrectomy (RN) for analyses. Primary outcome was development of de-novo estimated glomerular filtration rate (eGFR)<45 mL/min/1.73 m2. Secondary outcomes were de-novo eGFR<60 and ΔeGFR between diagnosis and last follow-up. Cox proportional hazards was used to elucidate predictors for de-novo eGFR<60 and <45. Linear regression was utilized to analyze ΔeGFR. Kaplan-Meier Analysis (KMA) was performed to analyze 5-year freedom from de-novo eGFR<60 and <45. RESULTS We analyzed 969 patients (RN=429/PN=540; median follow-up 24.0 months). RN patients had lower BMI (P<0.001) and larger tumor size (P<0.001). Overall postoperative complication rate was higher for PN (P<0.001), but there was no difference in major complications (Clavien III-IV; P=0.702). MVA demonstrated age (HR=1.05, P<0.001), tumor-size (HR=1.05, P=0.046), RN (HR=2.57, P<0.001), and BMI (HR=1.04, P=0.001) to be associated with risk for de-novo eGFR<60 mL/min/1.73 m2. Age (HR=1.03, P<0.001), BMI (HR=1.06, P<0.001), baseline eGFR (HR=0.99, P=0.002), tumor size (HR=1.07, P=0.007) and RN (HR=2.39, P<0.001) were risk factors for de-novo eGFR<45 mL/min/1.73 m2. RN (B=-10.89, P<0.001) was associated with greater ΔeGFR. KMA revealed worse 5-year freedom from de-novo eGFR<60 (71% vs. 33%, P<0.001) and de-novo eGFR<45 (79% vs. 65%, P<0.001) for RN. CONCLUSIONS PN provides functional benefit in selected patients with CRM without significant increase in major complications compared to RN, and should be considered when technically feasible.
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Affiliation(s)
- Clara Cerrato
- Department of Urology, UC San Diego School of Medicine, La Jolla, CA, USA
- Department of Urology, Azienda Ospedaliera Universitaria Integrata, University of Verona, Verona, Italy
| | - Margaret F Meagher
- Department of Urology, UC San Diego School of Medicine, La Jolla, CA, USA
| | | | - Giuseppe Simone
- Department of Urology, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Bo Yang
- Department of Urology, Changhai Hospital, Shanghai, China
| | - Robert G Uzzo
- Division of Urology and Urologic Oncology, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Alexander Kutikov
- Division of Urology and Urologic Oncology, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Francesco Porpiglia
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
| | - Umberto Capitanio
- Division of Experimental Oncology, Unit of Urology, Urological Research Institute (URI), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Francesco Montorsi
- Division of Experimental Oncology, Unit of Urology, Urological Research Institute (URI), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Alp T Beksac
- Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Dhruv Puri
- Department of Urology, UC San Diego School of Medicine, La Jolla, CA, USA
| | - Mimi Nguyen
- Department of Urology, UC San Diego School of Medicine, La Jolla, CA, USA
| | - Luke Wang
- Department of Urology, UC San Diego School of Medicine, La Jolla, CA, USA
| | - Kevin Hakimi
- Department of Urology, UC San Diego School of Medicine, La Jolla, CA, USA
| | - Sohail Dhanji
- Department of Urology, UC San Diego School of Medicine, La Jolla, CA, USA
| | - Franklin Liu
- Department of Urology, UC San Diego School of Medicine, La Jolla, CA, USA
| | - Maria A Cerruto
- Department of Urology, Azienda Ospedaliera Universitaria Integrata, University of Verona, Verona, Italy
| | | | | | - Clayton Lau
- Division of Urology and Urologic Oncology, City of Hope Medical Center, Duarte, CA, USA
| | - Aron Monish
- Institute of Urology, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | - Daniel Eun
- Department of Urology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA
| | | | - Carmen Mir
- Department of Urology, Hospital Universitario de la Ribera, Valencia, Spain
| | - Chandru Sundaram
- Department of Urology, Indiana University Health, Indianapolis, IN, USA
| | - Alessandro Antonelli
- Department of Urology, Azienda Ospedaliera Universitaria Integrata, University of Verona, Verona, Italy
| | - Jihad Kaouk
- Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Ithaar H Derweesh
- Department of Urology, UC San Diego School of Medicine, La Jolla, CA, USA -
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20
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Turri F, Piramide F, Dell'oglio P, de Groote R, Lambert E, di Maida F, Knipper S, Wuernschimmel C, Andras I, Liakos N, Larcher A, Rocco B, Sighinolfi C. Comment on: "Techniques and outcomes of robot-assisted partial nephrectomy for the treatment of multiple ipsilateral renal masses". Minerva Urol Nephrol 2023; 75:398-400. [PMID: 37221828 DOI: 10.23736/s2724-6051.23.05353-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Affiliation(s)
- Filippo Turri
- Department of Urology, ASST Santi Paolo e Carlo, University of Milan, Milan, Italy
| | - Federico Piramide
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy -
| | - Paolo Dell'oglio
- Department of Urology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Ruben de Groote
- Department of Urology, Ghent University Hospital, Ghent, Belgium
| | - Edward Lambert
- Department of Urology, Ghent University Hospital, Ghent, Belgium
| | - Fabrizio di Maida
- Department of Urology, Careggi Hospital, University of Florence, Florence, Italy
| | - Sophie Knipper
- Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | | | - Iulia Andras
- Department of Urology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Nikolaos Liakos
- Department of Urology, St. Antonius Hospital Gronau, Gronau, Germany
| | - Alessandro Larcher
- Division of Experimental Oncology, Department of Urology, Urological Research Institute (URI), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Bernardo Rocco
- Department of Urology, ASST Santi Paolo e Carlo, University of Milan, Milan, Italy
| | - Chiara Sighinolfi
- Department of Urology, ASST Santi Paolo e Carlo, University of Milan, Milan, Italy
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21
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Cannon PC, Ferguson JM, Pitt EB, Shrand JA, Setia SA, Nimmagadda N, Barth EJ, Kavoussi NL, Galloway RL, Herrell SD, Webster RJ. A Safe Framework for Quantitative In Vivo Human Evaluation of Image Guidance. IEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY 2023; 5:133-139. [PMID: 38487093 PMCID: PMC10939321 DOI: 10.1109/ojemb.2023.3271853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/16/2023] [Accepted: 03/27/2023] [Indexed: 03/17/2024] Open
Abstract
Goal: We present a new framework for in vivo image guidance evaluation and provide a case study on robotic partial nephrectomy. Methods: This framework (called the "bystander protocol") involves two surgeons, one who solely performs the therapeutic process without image guidance, and another who solely periodically collects data to evaluate image guidance. This isolates the evaluation from the therapy, so that in-development image guidance systems can be tested without risk of negatively impacting the standard of care. We provide a case study applying this protocol in clinical cases during robotic partial nephrectomy surgery. Results: The bystander protocol was performed successfully in 6 patient cases. We find average lesion centroid localization error with our IGS system to be 6.5 mm in vivo compared to our prior result of 3.0 mm in phantoms. Conclusions: The bystander protocol is a safe, effective method for testing in-development image guidance systems in human subjects.
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Affiliation(s)
| | | | | | | | | | - Naren Nimmagadda
- Vanderbilt University Medical CenterNashvilleTN37232USA
- The Johns Hopkins University School of MedicineBaltimoreMD21287USA
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22
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Amparore D, Piramide F, Verri P, Checcucci E, De Cillis S, Piana A, Volpi G, Burgio M, Busacca G, Colombo M, Fiori C, Porpiglia F. New Generation of 3D Virtual Models with Perfusional Zones: Perioperative Assistance for the Best Pedicle Management during Robotic Partial Nephrectomy. Curr Oncol 2023; 30:4021-4032. [PMID: 37185417 PMCID: PMC10136700 DOI: 10.3390/curroncol30040304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 03/24/2023] [Accepted: 03/29/2023] [Indexed: 04/05/2023] Open
Abstract
Selective clamping during robot-assisted partial nephrectomy (RAPN) may reduce ischemia-related functional impairment. The intraoperative use of 3D-virtual models (3DVMs) can improve surgical planning, resulting in a greater success rate for selective clamping. Our goal is to introduce a new generation of 3DVMs, which consider the perfusion volumes of the kidney. Patients listed for RAPN from 2021 to 2022 were recruited. A selective clamping strategy was designed and intraoperatively performed based on the specifically generated 3DVMs. The effectiveness of selective clamping was evaluated using near-infrared-fluorescence imaging (NIRF) and 3DVM. Perfusion areas extensions were compared, and relevant preoperative characteristics were analyzed. In 61 of 80 (76.25%) cases, selective clamping was performed. The concordance between the 3DVM areas and the NIRF-enhanced areas was verified (k = 0.91). According to the distribution of perfused areas crossing the tumor, there were one, two, three, four, and five crossing areas, with relative perfusion rates of 13.75%, 35%, 32.5%, 13.75%, and 5%, respectively. Lesion diameter and mesorenal location were the only factors related to a higher number (>3) of perfusion volumes crossing the lesion. The implementation of mathematical algorithms to 3DVMs allows for precise estimation of the perfusion zone of each arterial branch feeding the organ, leading to the performance of safe and effective pedicle management planning.
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Affiliation(s)
- Daniele Amparore
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Federico Piramide
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Paolo Verri
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy
| | - Sabrina De Cillis
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Alberto Piana
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Gabriele Volpi
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy
| | - Mariano Burgio
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Giovanni Busacca
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Marco Colombo
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Cristian Fiori
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Francesco Porpiglia
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
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23
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Gallo F, Sforza S, Mari A, Luciani L, Schenone M, Minervini A. Robotic Partial Nephrectomy for Bilateral Renal Masses. Curr Urol Rep 2023; 24:157-163. [PMID: 36538282 DOI: 10.1007/s11934-022-01143-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/22/2022] [Indexed: 12/25/2022]
Abstract
PURPOSE OF REVIEW There are very few data on patients undergoing robot-assisted partial nephrectomy (RAPN) for bilateral renal masses. The aim of this review is to update the literature and discuss the controversial points on this topic. RECENT FINDINGS Nine papers have been published regarding RAPN for bilateral renal masses. In particular, five papers were case reports while the remaining four reported patient series. Concerning the outcomes, all these papers highlighted the safety, feasibility, and efficacy of bilateral RAPN for bilateral renal masses. The literature confirmed RAPN as an optimal procedure for the treatment of bilateral renal masses. However, these outcomes mainly derived from selected group of patients who underwent complex surgical procedures by expert robotic surgeons at high volume centers and cannot be generalizable to all categories of patients or centers. The simultaneous bilateral approach resulted feasible showing some advantages and without higher complications than a staged procedure in particular when clampless or selective clamping techniques were performed.
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Affiliation(s)
- Fabrizio Gallo
- Department of Urology, San Paolo Hospital, Savona, Italy.
| | - Simone Sforza
- Department of Urology, Careggi University Hospital, Florence, Italy
| | - Andrea Mari
- Department of Urology, Careggi University Hospital, Florence, Italy
| | | | | | - Andrea Minervini
- Department of Urology, Careggi University Hospital, Florence, Italy
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24
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Checcucci E, Piramide F, De Cillis S, Volpi G, Piana A, Verri P, Bellin A, Di Dio M, Fiori C, Porpiglia F, Amparore D. Health Information Technology Usability Evaluation Scale (Health-ITUES) and User-Experience Questionnaire (UEQ) for 3D Intraoperative Cognitive Navigation (ICON3D TM) System for Urological Procedures. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:medicina59030624. [PMID: 36984625 PMCID: PMC10057936 DOI: 10.3390/medicina59030624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 03/12/2023] [Accepted: 03/13/2023] [Indexed: 03/30/2023]
Abstract
Backgound and objectives: In recent years, the adoption of 3D models for surgical planning and intraoperative guidance has gained a wide diffusion. The aim of this study was to evaluate the surgeons' perception and usability of ICON3DTM platform for robotic and laparoscopic urological surgical procedures. Materials and Methods: During the 10th edition of the Techno-Urology Meeting, surgeons and attendees had the opportunity to test the new ICON3DTM platform. The capability of the user to manipulate the model with hands/mouse, the software usability, the quality of the 3D model's reproduction, and the quality of its use during the surgery were evaluated with the Health Information Technology Usability Evaluation Scale (Health-ITUES) and the User-Experience Questionnaire (UEQ). Results: Fifty-three participants responded to the questionnaires. Based on the answers to the Health-ITUES questionnaire, ICON3DTM resulted to have a positive additional value in presurgical/surgical planning with 43.4% and 39.6% of responders that rated 4 (agree) and 5 (strongly agree), respectively. Regarding the UEQ questionnaire, both mouse and infrared hand-tracking system resulted to be easy to use for 99% of the responders, while the software resulted to be easy to use for 93.4% of the responders. Conclusions: In conclusion, ICON3DTM has been widely appreciated by urologists thanks to its various applications, from preoperative planning to its support for intraoperative decision-making in both robot-assisted and laparoscopic settings.
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Affiliation(s)
- Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy
| | - Federico Piramide
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, 10043 Orbassano, Italy
| | - Sabrina De Cillis
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, 10043 Orbassano, Italy
| | - Gabriele Volpi
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy
| | - Alberto Piana
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, 10043 Orbassano, Italy
| | - Paolo Verri
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, 10043 Orbassano, Italy
| | - Andrea Bellin
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, 10043 Orbassano, Italy
| | - Michele Di Dio
- Division of Urology, Department of Surgery, Annunziata Hospital, 10060 Cosenza, Italy
| | - Cristian Fiori
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, 10043 Orbassano, Italy
| | - Francesco Porpiglia
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, 10043 Orbassano, Italy
| | - Daniele Amparore
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, 10043 Orbassano, Italy
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De Backer P, Van Praet C, Simoens J, Peraire Lores M, Creemers H, Mestdagh K, Allaeys C, Vermijs S, Piazza P, Mottaran A, Bravi CA, Paciotti M, Sarchi L, Farinha R, Puliatti S, Cisternino F, Ferraguti F, Debbaut C, De Naeyer G, Decaestecker K, Mottrie A. Improving Augmented Reality Through Deep Learning: Real-time Instrument Delineation in Robotic Renal Surgery. Eur Urol 2023:S0302-2838(23)02633-7. [PMID: 36941148 DOI: 10.1016/j.eururo.2023.02.024] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 01/25/2023] [Accepted: 02/13/2023] [Indexed: 03/23/2023]
Abstract
Several barriers prevent the integration and adoption of augmented reality (AR) in robotic renal surgery despite the increased availability of virtual three-dimensional (3D) models. Apart from correct model alignment and deformation, not all instruments are clearly visible in AR. Superimposition of a 3D model on top of the surgical stream, including the instruments, can result in a potentially hazardous surgical situation. We demonstrate real-time instrument detection during AR-guided robot-assisted partial nephrectomy and show the generalization of our algorithm to AR-guided robot-assisted kidney transplantation. We developed an algorithm using deep learning networks to detect all nonorganic items. This algorithm learned to extract this information for 65 927 manually labeled instruments on 15 100 frames. Our setup, which runs on a standalone laptop, was deployed in three different hospitals and used by four different surgeons. Instrument detection is a simple and feasible way to enhance the safety of AR-guided surgery. Future investigations should strive to optimize efficient video processing to minimize the 0.5-s delay currently experienced. General AR applications also need further optimization, including detection and tracking of organ deformation, for full clinical implementation.
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Affiliation(s)
- Pieter De Backer
- ORSI Academy, Melle, Belgium; IBiTech-Biommeda, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium; Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Department of Urology, ERN eUROGEN accredited centre, Ghent University Hospital, Ghent, Belgium; Cancer Research Institute Ghent, Ghent University, Ghent, Belgium.
| | - Charles Van Praet
- Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Department of Urology, ERN eUROGEN accredited centre, Ghent University Hospital, Ghent, Belgium
| | | | | | - Heleen Creemers
- Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Kenzo Mestdagh
- Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Charlotte Allaeys
- Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Department of Urology, ERN eUROGEN accredited centre, Ghent University Hospital, Ghent, Belgium
| | - Saar Vermijs
- IBiTech-Biommeda, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium; Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Cancer Research Institute Ghent, Ghent University, Ghent, Belgium
| | - Pietro Piazza
- ORSI Academy, Melle, Belgium; Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Angelo Mottaran
- ORSI Academy, Melle, Belgium; Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Carlo A Bravi
- ORSI Academy, Melle, Belgium; Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium; Division of Oncology/Unit of Urology, Urological Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Marco Paciotti
- ORSI Academy, Melle, Belgium; Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium; Department of Urology, Humanitas Clinical and Research Center, Rozzano, Milan, Italy
| | - Luca Sarchi
- ORSI Academy, Melle, Belgium; Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium
| | - Rui Farinha
- ORSI Academy, Melle, Belgium; Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium
| | - Stefano Puliatti
- ORSI Academy, Melle, Belgium; Department of Urology, University of Modena and Reggio Emilia, Modena, Italy
| | - Francesco Cisternino
- Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Modena, Italy
| | - Federica Ferraguti
- Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Modena, Italy
| | - Charlotte Debbaut
- IBiTech-Biommeda, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium; Cancer Research Institute Ghent, Ghent University, Ghent, Belgium
| | - Geert De Naeyer
- Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium
| | - Karel Decaestecker
- Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Department of Urology, ERN eUROGEN accredited centre, Ghent University Hospital, Ghent, Belgium; Department of Urology, AZ Maria Middelares Hospital, Ghent, Belgium
| | - Alexandre Mottrie
- ORSI Academy, Melle, Belgium; Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium
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Zhang J, Lu V, Khanduja V. The impact of extended reality on surgery: a scoping review. INTERNATIONAL ORTHOPAEDICS 2023; 47:611-621. [PMID: 36645474 PMCID: PMC9841146 DOI: 10.1007/s00264-022-05663-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 12/03/2022] [Indexed: 01/17/2023]
Abstract
PURPOSE Extended reality (XR) is defined as a spectrum of technologies that range from purely virtual environments to enhanced real-world environments. In the past two decades, XR-assisted surgery has seen an increase in its use and also in research and development. This scoping review aims to map out the historical trends in these technologies and their future prospects, with an emphasis on the reported outcomes and ethical considerations on the use of these technologies. METHODS A systematic search of PubMed, Scopus, and Embase for literature related to XR-assisted surgery and telesurgery was performed using Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) guidelines. Primary studies, peer-reviewed articles that described procedures performed by surgeons on human subjects and cadavers, as well as studies describing general surgical education, were included. Non-surgical procedures, bedside procedures, veterinary procedures, procedures performed by medical students, and review articles were excluded. Studies were classified into the following categories: impact on surgery (pre-operative planning and intra-operative navigation/guidance), impact on the patient (pain and anxiety), and impact on the surgeon (surgical training and surgeon confidence). RESULTS One hundred and sixty-eight studies were included for analysis. Thirty-one studies investigated the use of XR for pre-operative planning concluded that virtual reality (VR) enhanced the surgeon's spatial awareness of important anatomical landmarks. This leads to shorter operating sessions and decreases surgical insult. Forty-nine studies explored the use of XR for intra-operative planning. They noted that augmented reality (AR) headsets highlight key landmarks, as well as important structures to avoid, which lowers the chance of accidental surgical trauma. Eleven studies investigated patients' pain and noted that VR is able to generate a meditative state. This is beneficial for patients, as it reduces the need for analgesics. Ten studies commented on patient anxiety, suggesting that VR is unsuccessful at altering patients' physiological parameters such as mean arterial blood pressure or cortisol levels. Sixty studies investigated surgical training whilst seven studies suggested that the use of XR-assisted technology increased surgeon confidence. CONCLUSION The growth of XR-assisted surgery is driven by advances in hardware and software. Whilst augmented virtuality and mixed reality are underexplored, the use of VR is growing especially in the fields of surgical training and pre-operative planning. Real-time intra-operative guidance is key for surgical precision, which is being supplemented with AR technology. XR-assisted surgery is likely to undertake a greater role in the near future, given the effect of COVID-19 limiting physical presence and the increasing complexity of surgical procedures.
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Affiliation(s)
- James Zhang
- School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SP UK
| | - Victor Lu
- School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SP UK
| | - Vikas Khanduja
- Young Adult Hip Service, Department of Trauma and Orthopaedics, Addenbrooke's Hospital, Cambridge University Hospital, Hills Road, Cambridge, CB2 0QQ, UK.
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Romao RLP, van der Steeg AFW, Malek M, Irtan S, Gow K, Ghandour K, Biasoni D, Davidoff A, Pachl M. Technical advances in the surgical management of Wilms tumors in children. Pediatr Blood Cancer 2023; 70 Suppl 2:e30267. [PMID: 36815577 DOI: 10.1002/pbc.30267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 12/19/2022] [Accepted: 01/11/2023] [Indexed: 02/24/2023]
Abstract
Surgery is one of the cornerstones of Wilms tumor treatment. In this article, we present technical advancements that are finding their way into the armamentarium of pediatric cancer surgeons. We discuss the current approaches, challenges, opportunities, and future directions of minimally invasive surgery (laparoscopic and robotics), image-guided surgery, and fluorescence-guided surgery. Furthermore, we discuss the use of intraoperative ultrasonography, as well as the use of new techniques to improve the quality of lymph node sampling.
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Affiliation(s)
- Rodrigo L P Romao
- Departments of Surgery and Urology, IWK Health, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Alida F W van der Steeg
- Department of Pediatric Surgery, Princess Maxima Center for Pediatric Oncology, Utrecht, Netherlands
| | - Marcus Malek
- Division of Pediatric General and Thoracic Surgery, University of Pittsburgh Medical Center, Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Sabine Irtan
- Department of Visceral and Neonatal Pediatric Surgery, Sorbonne Université, Armand-Trousseau Hospital - APHP, Paris, France
| | - Kenneth Gow
- Division of Pediatric General and Thoracic Surgery, Seattle Children's Hospital, University of Washington, Seattle, Washington, USA
| | - Khalil Ghandour
- Department of Surgery, King Hussein Cancer Foundation and Center, Amman, Jordan
| | - David Biasoni
- Department of Pediatric Surgery, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy
| | - Andrew Davidoff
- Department of Surgery, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Max Pachl
- Department of Pediatric Surgery, Birmingham Women's and Children's Hospital, Birmingham, UK
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Michiels C, Khene ZE, Prudhomme T, Boulenger de Hauteclocque A, Cornelis FH, Percot M, Simeon H, Dupitout L, Bensadoun H, Capon G, Alezra E, Estrade V, Bladou F, Robert G, Ferriere JM, Grenier N, Doumerc N, Bensalah K, Bernhard JC. 3D-Image guided robotic-assisted partial nephrectomy: a multi-institutional propensity score-matched analysis (UroCCR study 51). World J Urol 2023; 41:303-313. [PMID: 33811291 DOI: 10.1007/s00345-021-03645-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 02/19/2021] [Indexed: 01/20/2023] Open
Abstract
PURPOSE Robot-assisted partial nephrectomy (RAPN) is a difficult procedure with risk of significant perioperative complications. The objective was to evaluate the impact of preoperative planning and intraoperative guidance with 3D model reconstructions on perioperative outcomes of RAPN. METHODS We conducted a retrospective analysis of all patients who underwent RAPN for kidney tumor by three high-volume expert surgeons from academic centers. Clinical data were collected prospectively after written consent into the French kidney cancer network database UroCCR (CNIL-DR 2013-206; NCT03293563). Our cohort was divided into two groups: 3D-Image guided RAPN group (3D-IGRAPN) and control group. A propensity score according to age, pre-operative renal function and RENAL tumor complexity score was used. Both surgical techniques were compared in terms of perioperative outcomes. RESULTS The initial study cohort included 230 3D-IGRAPN and 415 control RAPN. Before propensity-score matching, patients in the 3D-IGRAPN group had a larger tumor (4.3 cm vs. 3.5 cm, P < 0.001) and higher RENAL complexity score (9 vs. 8, P < 0.001). Following propensity-score matching, there were 157 patients in both groups. The rate of major complications was lower for patients in the 3D-IGRAPN group (3.8% vs. 9.5%, P = 0.04). The median percentage of eGFR variation recorded at first follow-up was lower in the 3D-IGRAPN group (- 5.6% vs. - 10.5%, P = 0.002). The trifecta achievement rate was higher in the 3D-IGRAPN group (55.7% vs. 45.1%; P = 0.005). CONCLUSION Three-dimensional kidney reconstructions use for pre-operative planning and intraoperative surgical guidance lowers the risk of complications and improve perioperative clinical outcomes of RAPN.
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Affiliation(s)
- Clément Michiels
- Department of Urology, Bordeaux University Hospital, Bordeaux, France.
| | | | - Thomas Prudhomme
- Department of Urology, Toulouse University Hospital, Toulouse, France
| | | | - François H Cornelis
- Department of Radiology, Bordeaux University Hospital, Bordeaux, France.,Department of Radiology, Tenon Hospital, APHP, Paris, France
| | - Mélanie Percot
- Department of Urology, Bordeaux University Hospital, Bordeaux, France
| | - Hélène Simeon
- Department of Urology, Bordeaux University Hospital, Bordeaux, France
| | - Laure Dupitout
- Department of Urology, Bordeaux University Hospital, Bordeaux, France
| | - Henri Bensadoun
- Department of Urology, Bordeaux University Hospital, Bordeaux, France
| | - Grégoire Capon
- Department of Urology, Bordeaux University Hospital, Bordeaux, France
| | - Eric Alezra
- Department of Urology, Bordeaux University Hospital, Bordeaux, France
| | - Vincent Estrade
- Department of Urology, Bordeaux University Hospital, Bordeaux, France
| | - Franck Bladou
- Department of Urology, Bordeaux University Hospital, Bordeaux, France
| | - Grégoire Robert
- Department of Urology, Bordeaux University Hospital, Bordeaux, France
| | | | - Nicolas Grenier
- Department of Radiology, Bordeaux University Hospital, Bordeaux, France
| | - Nicolas Doumerc
- Department of Urology, Toulouse University Hospital, Toulouse, France
| | - Karim Bensalah
- Department of Urology, Rennes University Hospital, Rennes, France
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A survey of augmented reality methods to guide minimally invasive partial nephrectomy. World J Urol 2023; 41:335-343. [PMID: 35776173 DOI: 10.1007/s00345-022-04078-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 05/21/2022] [Indexed: 10/17/2022] Open
Abstract
INTRODUCTION Minimally invasive partial nephrectomy (MIPN) has become the standard of care for localized kidney tumors over the past decade. The characteristics of each tumor, in particular its size and relationship with the excretory tract and vessels, allow one to judge its complexity and to attempt predicting the risk of complications. The recent development of virtual 3D model reconstruction and computer vision has opened the way to image-guided surgery and augmented reality (AR). OBJECTIVE Our objective was to perform a systematic review to list and describe the different AR techniques proposed to support PN. MATERIALS AND METHODS The systematic review of the literature was performed on 12/04/22, using the keywords "nephrectomy" and "augmented reality" on Embase and Medline. Articles were considered if they reported surgical outcomes when using AR with virtual image overlay on real vision, during ex vivo or in vivo MIPN. We classified them according to the registration technique they use. RESULTS We found 16 articles describing an AR technique during MIPN procedures that met the eligibility criteria. A moderate to high risk of bias was recorded for all the studies. We classified registration methods into three main families, of which the most promising one seems to be surface-based registration. CONCLUSION Despite promising results, there do not exist studies showing an improvement in clinical outcomes using AR. The ideal AR technique is probably yet to be established, as several designs are still being actively explored. More clinical data will be required to establish the potential contribution of this technology to MIPN.
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Xiao Y, Shan ZJ, Yang JF, Len JJ, Yu YH, Yang ML. Nephrometric scoring system: Recent advances and outlooks. Urol Oncol 2023; 41:15-26. [PMID: 35907706 DOI: 10.1016/j.urolonc.2022.06.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 05/09/2022] [Accepted: 06/27/2022] [Indexed: 11/28/2022]
Abstract
A nephrometry scoring system is a key standard to evaluate the feasibility of partial nephrectomy (PN). Whether based on two-dimensional or three-dimensional images, simplicity, effectiveness, and practicality are the keys to the nephrometric scoring system. Since the emergence of RENAL score in 2009, numerous scoring systems based on different anatomical parameters are established to seek accurately and few parameters to assess the risk of PN and complications. This study aimed to achieve a three-game winning streak in PN more easily and efficiently (negative resection margin, maximum preservation of normal nephron function, and avoiding short-term and long-term complications). Using PubMed, we counted 28 kinds of nephrometric scoring systems. We considered only English literatures published and excluded editorials, commentaries, and meeting abstracts. To the best of our knowledge, this is to date and most comprehensive summary as well as an outlook of the nephrometric scoring system.
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Affiliation(s)
- Yu Xiao
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China; Department of Urology, The First People's Hospital of Yunnan Province, Kunming, Yunnan, China
| | - Zu-Juan Shan
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China; Department of Urology, The First People's Hospital of Yunnan Province, Kunming, Yunnan, China
| | - Jun-Feng Yang
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China; Department of Urology, The First People's Hospital of Yunnan Province, Kunming, Yunnan, China
| | - Jin-Jun Len
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China; Department of Urology, The First People's Hospital of Yunnan Province, Kunming, Yunnan, China
| | - Yan-Hong Yu
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China; Department of Urology, The First People's Hospital of Yunnan Province, Kunming, Yunnan, China.
| | - Mao-Lin Yang
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China; Department of Urology, The First People's Hospital of Yunnan Province, Kunming, Yunnan, China
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Cheng C, Lu M, Zhang Y, Hu X. Effect of augmented reality navigation technology on perioperative safety in partial nephrectomies: A meta-analysis and systematic review. Front Surg 2023; 10:1067275. [PMID: 37123539 PMCID: PMC10130447 DOI: 10.3389/fsurg.2023.1067275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 03/27/2023] [Indexed: 05/02/2023] Open
Abstract
Aim To evaluate the impact of augmented reality surgical navigation (ARSN) technology on short-term outcomes of partial nephrectomy (PN). Methods A systematic literature search was conducted in PubMed, Embase, Cochrane, and Web of Science for eligible studies published through March 28, 2022. Two researchers independently performed the article screening, data extraction and quality review. Data analysis was performed using Cochrane Review Manager software. Results A total of 583 patients from eight studies were included in the analysis, with 313 in the ARSN-assisted PN group (AR group) and 270 in the conventional PN group (NAR group). ARSN-assisted PN showed better outcomes than conventional surgery in terms of operative time, estimated blood loss, global ischemia rate, warm ischemia time, and enucleation rate. However, there were no significant differences in the rate of Conversion to radical nephrectomy (RN), postoperative estimated glomerular filtration rate (eGFR), positive margin rate, and postoperative complication rate. Conclusion The utilization of ARSN can improve the perioperative safety of PN. Compared with conventional PN, ARSN-assisted PN can reduce intraoperative blood loss, shorten operative time, and improve renal ischemia. Although direct evidence is lacking, our results still suggest a potential advantage of ARSN in improving renal recovery after PN. However, as the ARSN system is still in an exploratory stage, its relevance in PN have been poorly reported. Additional high-quality randomized controlled trial (RCT) studies will be required to confirm the effect of ARSN on PN. Systematic Review Registration https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=301798, identifier PROSPERO ID: CRD42022301798.
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van Leeuwen FWB, van der Hage JA. Where Robotic Surgery Meets the Metaverse. Cancers (Basel) 2022; 14:cancers14246161. [PMID: 36551645 PMCID: PMC9776294 DOI: 10.3390/cancers14246161] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 12/05/2022] [Indexed: 12/15/2022] Open
Abstract
With a focus on hepatobiliary surgery, the review by Giannone et al [...].
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Affiliation(s)
- Fijs W. B. van Leeuwen
- Interventional Molecular Imaging Laboratory, Department of Radiology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands
- Correspondence:
| | - Jos A. van der Hage
- Department of Sugery, Leiden University Medical Center, 2300 RC Leiden, The Netherlands
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Establishing a Point-of-Care Virtual Planning and 3D Printing Program. Semin Plast Surg 2022; 36:133-148. [PMID: 36506280 PMCID: PMC9729064 DOI: 10.1055/s-0042-1754351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Virtual surgical planning (VSP) and three-dimensional (3D) printing have become a standard of care at our institution, transforming the surgical care of complex patients. Patient-specific, anatomic models and surgical guides are clinically used to improve multidisciplinary communication, presurgical planning, intraoperative guidance, and the patient informed consent. Recent innovations have allowed both VSP and 3D printing to become more accessible to various sized hospital systems. Insourcing such work has several advantages including quicker turnaround times and increased innovation through collaborative multidisciplinary teams. Centralizing 3D printing programs at the point-of-care provides a greater cost-efficient investment for institutions. The following article will detail capital equipment needs, institutional structure, operational personnel, and other considerations necessary in the establishment of a POC manufacturing program.
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Piramide F, Kowalewski KF, Cacciamani G, Rivero Belenchon I, Taratkin M, Carbonara U, Marchioni M, De Groote R, Knipper S, Pecoraro A, Turri F, Dell'Oglio P, Puliatti S, Amparore D, Volpi G, Campi R, Larcher A, Mottrie A, Breda A, Minervini A, Ghazi A, Dasgupta P, Gozen A, Autorino R, Fiori C, Di Dio M, Gomez Rivas J, Porpiglia F, Checcucci E. Three-dimensional Model-assisted Minimally Invasive Partial Nephrectomy: A Systematic Review with Meta-analysis of Comparative Studies. Eur Urol Oncol 2022; 5:640-650. [PMID: 36216739 DOI: 10.1016/j.euo.2022.09.003] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Revised: 08/16/2022] [Accepted: 09/21/2022] [Indexed: 01/26/2023]
Abstract
CONTEXT Use of three-dimensional (3D) guidance for nephron-sparing surgery (NSS) has increased in popularity, especially for laparoscopic and robotic approaches. Different 3D visualization modalities have been developed as promising new tools for surgical planning and intraoperative navigation. OBJECTIVES To summarize and evaluate the impact of 3D models on minimally invasive NSS in terms of perioperative, functional, and oncological outcomes. EVIDENCE ACQUISITION A systematic literature search was conducted in December 2021 using the Medline (PubMed), Embase (Ovid), Scopus, and Web of Science databases. The protocol was registered on PROSPERO (CRD42022300948). The search strategy used the PICOS (Population, Intervention, Comparison, Outcome, Study design) criteria and article selection was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The risk of bias and the quality of the articles included were assessed. A dedicated data extraction form was used to collect the data of interest. Meta-analysis was performed using the Mantel-Haenszel method for binary outcomes, with results summarized as the odds ratio (OR), and the inverse variance method for continuous data, with results reported as the mean difference (MD). All effect estimates are reported with the 95% confidence interval (CI) and p ≤ 0.05 was considered statistically significant. All analyses were performed using R software and the meta package. EVIDENCE SYNTHESIS The initial electronic search identified 450 papers, of which 17 met the inclusion criteria and were included in the analysis. Use of 3D technology led to a significant reduction in the global ischemia rate (OR 0.22, 95% CI 0.07-0.76; p = 0.02) and facilitated more frequent enucleation (OR 2.54, 95% CI 1.36-4.74; p < 0.01) and less frequent opening of the collecting system (OR 0.36, 95% CI 0.15-0.89; p = 0.03) and was associated with less blood loss (MD 23.1 ml, 95% CI 31.8-14.4; p < 0.01). 3D guidance for NSS was associated with a significant reduction in the transfusion rate (OR 0.20, 95% CI 0.07-0.56; p < 0.01). There were no significant differences in rates of conversion to radical nephrectomy, minor and major complications, change in glomerular filtration rate, or surgical margins (all p > 0.05). CONCLUSIONS 3D guidance for NSS is associated with lower rates of detriment and surgical injury to the kidney. Specifically, a lower amount of nontumor renal parenchyma is exposed to ischemia or sacrificed during resection, and opening of the collecting system is less frequent. However, use of 3D technology does not lead to significant improvements in oncological or functional outcomes. PATIENT SUMMARY We reviewed the use of three-dimensional tools for minimally invasive surgery for partial removal of the kidney in patients with kidney cancer. The evidence suggests that these tools have benefits during surgery, but do not lead to significant improvements in cancer control or functional outcomes for patients.
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Affiliation(s)
- Federico Piramide
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy; European Association of Urology Young Academic Urologists Robotic Surgery Working Group, Arnhem, The Netherlands.
| | - Karl-Friedrich Kowalewski
- Department of Urology, University Medical Center Mannheim, University of Heidelberg, Mannheim, Germany; Association of Urology Young Academic Urologist-Urotechnology Working Party, Arnhem, The Netherlands
| | - Giovanni Cacciamani
- Association of Urology Young Academic Urologist-Urotechnology Working Party, Arnhem, The Netherlands; USC Institute of Urology, University of Southern California, Los Angeles, CA, USA
| | - Ines Rivero Belenchon
- Association of Urology Young Academic Urologist-Urotechnology Working Party, Arnhem, The Netherlands; Urology and Nephrology Department, Virgen del Rocío University Hospital, Seville, Spain
| | - Mark Taratkin
- Association of Urology Young Academic Urologist-Urotechnology Working Party, Arnhem, The Netherlands; Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia
| | - Umberto Carbonara
- European Association of Urology Young Academic Urologists Renal Cancer Working Group, Arnhem, The Netherlands; Department of Emergency and Organ Transplantation, Urology, Andrology and Kidney Transplantation Unit, University of Bari, Bari, Italy
| | - Michele Marchioni
- European Association of Urology Young Academic Urologists Renal Cancer Working Group, Arnhem, The Netherlands; Department of Urology, SS Annunziata Hospital, G. D'Annunzio University of Chieti, Chieti, Italy
| | - Ruben De Groote
- European Association of Urology Young Academic Urologists Robotic Surgery Working Group, Arnhem, The Netherlands; Department of Urology, OLV Hospital, Aalst, Belgium; ORSI Academy, Melle, Belgium
| | - Sophie Knipper
- European Association of Urology Young Academic Urologists Robotic Surgery Working Group, Arnhem, The Netherlands; Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Angela Pecoraro
- European Association of Urology Young Academic Urologists Renal Cancer Working Group, Arnhem, The Netherlands; Department of Urology, Hospital Pederzoli, Peschiera del Garda, Italy
| | - Filippo Turri
- European Association of Urology Young Academic Urologists Robotic Surgery Working Group, Arnhem, The Netherlands; Department of Urology, Nuovo Ospedale Civile S. Agostino Estense, University of Modena and Reggio Emilia, Modena, Italy
| | - Paolo Dell'Oglio
- European Association of Urology Young Academic Urologists Robotic Surgery Working Group, Arnhem, The Netherlands; Department of Urology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Stefano Puliatti
- Association of Urology Young Academic Urologist-Urotechnology Working Party, Arnhem, The Netherlands; Department of Urology, University of Modena and Reggio Emilia, Modena, Italy
| | - Daniele Amparore
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy; European Association of Urology Young Academic Urologists Renal Cancer Working Group, Arnhem, The Netherlands
| | - Gabriele Volpi
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Riccardo Campi
- European Association of Urology Young Academic Urologists Renal Cancer Working Group, Arnhem, The Netherlands; Unit of Urological Robotic Surgery and Renal Transplantation, Careggi Hospital, University of Florence, Florence, Italy
| | - Alessandro Larcher
- European Association of Urology Young Academic Urologists Robotic Surgery Working Group, Arnhem, The Netherlands; Unit of Urology, Division of Experimental Oncology, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Alex Mottrie
- Department of Urology, OLV Hospital, Aalst, Belgium; ORSI Academy, Melle, Belgium
| | - Alberto Breda
- Department of Urology, Fundació Puigvert, Autonomous University of Barcelona, Barcelona, Spain
| | - Andrea Minervini
- Unit of Oncologic Minimally-Invasive Urology and Andrology, Careggi Hospital, Florence, Italy; Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Ahmed Ghazi
- Department of Urology, University of Rochester Medical Center, Rochester, NY, USA
| | - Prokar Dasgupta
- Medical Research Council Centre for Transplantation, Guy's Hospital Campus, King's Health Partners, King's College London, London, UK
| | - Ali Gozen
- Trakya Tip Fak Hospital, Edirne, Turkey
| | | | - Cristian Fiori
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Michele Di Dio
- Department of Surgery, Division of Urology, SS Annunziata Hospital, Cosenza, Italy
| | - Juan Gomez Rivas
- Association of Urology Young Academic Urologist-Urotechnology Working Party, Arnhem, The Netherlands; Department of Urology, Hospital Clinico San Carlos, Madrid, Spain
| | - Francesco Porpiglia
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Enrico Checcucci
- Association of Urology Young Academic Urologist-Urotechnology Working Party, Arnhem, The Netherlands; Department of Surgery, FPO-IRCCS Candiolo Cancer Institute, Turin, Italy
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Bray G, Bahadori A, Mao D, Ranasinghe S, Tracey C. Benefits of Robotic Assisted vs. Traditional Laparoscopic Partial Nephrectomy: A Single Surgeon Comparative Study. J Clin Med 2022; 11:jcm11236974. [PMID: 36498549 PMCID: PMC9741158 DOI: 10.3390/jcm11236974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 11/18/2022] [Accepted: 11/22/2022] [Indexed: 11/29/2022] Open
Abstract
PURPOSE The current study aims to compare peri-operative and post-operative outcomes between robotic assisted vs. laparoscopic partial nephrectomy. Multiple reviews of the current literature have detailed the lack of single surgeon studies in this domain. To limit inter-operator bias, we utilise a single surgeon experienced in both approaches to reduce this bias seen in other multi-centre studies. METHODS AND MATERIALS We retrospectively compared patient demographics, tumour characteristics, peri-operative and post-operative outcomes of all partial nephrectomies undertaken by a single surgeon between 2014 and 2021 with experience in both laparoscopic and robotic surgery. The Da Vinci surgical system was utilized. Statistical analysis was carried out using GraphPad prism software version 7.03, San Diego, CA, USA. RESULTS Warm ischemia time was reduced by 2.6 min, length of stay reduced by 1.3 days and acute renal function deterioration was reduced by 55% with all these results being significant with robotic assisted partial nephrectomy compared to laparoscopic partial nephrectomy. CONCLUSION This study highlights the benefits of robotic assisted in comparison to laparoscopic partial nephrectomy. Further large-scale prospective studies and cost-benefit analysis of robotic assisted partial nephrectomy would be valuable in confirming these findings and justifying the usage against their financial cost.
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Affiliation(s)
- Gerard Bray
- Urology Department, Gold Coast University Hospital, Gold Coast, QLD 4215, Australia
- Correspondence: ; Tel.: +61-1300744284
| | - Arya Bahadori
- Urology Department, Gold Coast University Hospital, Gold Coast, QLD 4215, Australia
| | - Derek Mao
- Department of Medicine, Bond University, Gold Coast, QLD 4226, Australia
| | - Sachinka Ranasinghe
- Urology Department, Gold Coast University Hospital, Gold Coast, QLD 4215, Australia
| | - Christopher Tracey
- Urology Department, Gold Coast University Hospital, Gold Coast, QLD 4215, Australia
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Zhang S, Yang G, Qian J, Zhu X, Li J, Li P, He Y, Xu Y, Shao P, Wang Z. A novel 3D deep learning model to automatically demonstrate renal artery segmentation and its validation in nephron-sparing surgery. Front Oncol 2022; 12:997911. [PMID: 36313655 PMCID: PMC9614169 DOI: 10.3389/fonc.2022.997911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 09/28/2022] [Indexed: 12/02/2022] Open
Abstract
Purpose Nephron-sparing surgery (NSS) is a mainstream treatment for localized renal tumors. Segmental renal artery clamping (SRAC) is commonly used in NSS. Automatic and precise segmentations of renal artery trees are required to improve the workflow of SRAC in NSS. In this study, we developed a tridimensional kidney perfusion (TKP) model based on deep learning technique to automatically demonstrate renal artery segmentation, and verified the precision and feasibility during laparoscopic partial nephrectomy (PN). Methods The TKP model was established based on convolutional neural network (CNN), and the precision was validated in porcine models. From April 2018 to January 2020, TKP model was applied in laparoscopic PN in 131 patients with T1a tumors. Demographics, perioperative variables, and data from the TKP models were assessed. Indocyanine green (ICG) with near-infrared fluorescence (NIRF) imaging was applied after clamping and dice coefficient was used to evaluate the precision of the model. Results The precision of the TKP model was validated in porcine models with the mean dice coefficient of 0.82. Laparoscopic PN was successfully performed in all cases with segmental renal artery clamping (SRAC) under TKP model’s guidance. The mean operation time was 100.8 min; the median estimated blood loss was 110 ml. The ischemic regions recorded in NIRF imaging were highly consistent with the perfusion regions in the TKP models (mean dice coefficient = 0.81). Multivariate analysis revealed that the feeding lobar artery number was strongly correlated with tumor size and contact surface area; the supplying segmental arteries number correlated with tumor size. Conclusions Using the CNN technique, the TKP model is developed to automatically present the renal artery trees and precisely delineate the perfusion regions of different segmental arteries. The guidance of the TKP model is feasible and effective in nephron-sparing surgery.
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Affiliation(s)
- Shaobo Zhang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Guanyu Yang
- Key Laboratory of Computer Network and Information Integration, Southeast University, Ministry of Education, Nanjing, China
| | - Jian Qian
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaomei Zhu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jie Li
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Pu Li
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yuting He
- Key Laboratory of Computer Network and Information Integration, Southeast University, Ministry of Education, Nanjing, China
| | - Yi Xu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Pengfei Shao
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Pengfei Shao,
| | - Zengjun Wang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Piana A, Gallioli A, Amparore D, Diana P, Territo A, Campi R, Gaya JM, Guirado L, Checcucci E, Bellin A, Palou J, Serni S, Porpiglia F, Breda A. Three-dimensional Augmented Reality-guided Robotic-assisted Kidney Transplantation: Breaking the Limit of Atheromatic Plaques. Eur Urol 2022; 82:419-426. [PMID: 35985902 DOI: 10.1016/j.eururo.2022.07.003] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 06/15/2022] [Accepted: 07/11/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Robotic-assisted kidney transplantation (RAKT) has shown solid results as a minimally invasive alternative to the standard open approach (open kidney transplantation [OKT]). However, RAKT is still limited in those cases where the recipient's iliac vessels present atherosclerotic plaques, frequently found in elder patients and in those subjected to long-term hemodialysis. Unlike OKT, where the surgeon can palpate the arterial plaques, in minimally invasive surgery the haptic feedback is missing, making the vascular clamping and arteriotomy unsafe. OBJECTIVE To employ three-dimensional (3D) imaging reconstruction using augmented reality (AR) to intraoperatively locate the plaques during the crucial steps of kidney transplantation. DESIGN, SETTING, AND PARTICIPANTS Our study was conducted according to the Idea, Development, Exploration, Assessment, and Long-term follow-up (IDEAL) model for surgical innovation. Three-dimensional virtual models were obtained from high-accuracy computed tomography scan imaging and superimposed on the vessels during RAKT using the Da Vinci console software. SURGICAL PROCEDURE Three-dimensional AR-guided robotic-assisted kidney transplantation. MEASUREMENTS The correspondence of virtual models with the real anatomy of patients was assessed comparing vessels' and plaques' measures. RESULTS AND LIMITATIONS We tested the possibility of using the AR in the setting of vascular surgery by checking the correspondence of the virtual models to the real vessels. During the accuracy assessment, we investigated the anatomy of the iliac plaques and the capacity of the virtual models to correctly represent them. Finally, we tested the efficacy of the virtual model superimposition on the real vessels with plaques during RAKT in the recipients of living donor grafts. The main limitation consists in training needed to correctly superimpose virtual models on the real field. CONCLUSIONS The employment of 3D AR allowed surgeons to overcome one of the main limitations of RAKT, setting the foundation to expand its indications to patients with advanced atheromatic vascular disease. PATIENT SUMMARY The use of three-dimensional augmented reality guidance during kidney transplantation (KT) has the potential to "navigate" the surgeon during KT, allowing a safer procedure in patients with atheromatic vascular disease.
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Affiliation(s)
- Alberto Piana
- Department of Urology, Fundació Puigvert, Autonomous University of Barcelona, Barcelona, Spain; Department of Urology, "San Luigi Gonzaga" Hospital, University of Turin, Turin, Italy.
| | - Andrea Gallioli
- Department of Urology, Fundació Puigvert, Autonomous University of Barcelona, Barcelona, Spain
| | - Daniele Amparore
- Department of Urology, "San Luigi Gonzaga" Hospital, University of Turin, Turin, Italy
| | - Pietro Diana
- Department of Urology, Fundació Puigvert, Autonomous University of Barcelona, Barcelona, Spain
| | - Angelo Territo
- Department of Urology, Fundació Puigvert, Autonomous University of Barcelona, Barcelona, Spain
| | - Riccardo Campi
- Department of Urology, Careggi Hospital, University of Florence, Florence, Italy
| | - Josep Maria Gaya
- Department of Urology, Fundació Puigvert, Autonomous University of Barcelona, Barcelona, Spain
| | - Lluis Guirado
- Department of Nephrology, Fundació Puigvert, Autonomous University of Barcelona, Barcelona, Spain
| | - Enrico Checcucci
- Department of Urology, "San Luigi Gonzaga" Hospital, University of Turin, Turin, Italy
| | - Andrea Bellin
- Department of Urology, "San Luigi Gonzaga" Hospital, University of Turin, Turin, Italy
| | - Joan Palou
- Department of Urology, Fundació Puigvert, Autonomous University of Barcelona, Barcelona, Spain
| | - Sergio Serni
- Department of Urology, Careggi Hospital, University of Florence, Florence, Italy
| | - Francesco Porpiglia
- Department of Urology, "San Luigi Gonzaga" Hospital, University of Turin, Turin, Italy
| | - Alberto Breda
- Department of Urology, Fundació Puigvert, Autonomous University of Barcelona, Barcelona, Spain
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The intraoperative use of augmented and mixed reality technology to improve surgical outcomes: A systematic review. Int J Med Robot 2022; 18:e2450. [DOI: 10.1002/rcs.2450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 07/23/2022] [Accepted: 07/27/2022] [Indexed: 11/07/2022]
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Paraboschi I, Mantica G, Minoli DG, De Marco EA, Gnech M, Bebi C, Manzoni G, Berrettini A. Fluorescence-Guided Surgery and Novel Innovative Technologies for Improved Visualization in Pediatric Urology. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph191811194. [PMID: 36141458 PMCID: PMC9517607 DOI: 10.3390/ijerph191811194] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 08/27/2022] [Accepted: 09/02/2022] [Indexed: 05/30/2023]
Abstract
Fluorescence-guided surgery (FGS), three-dimensional (3D) imaging technologies, and other innovative devices are rapidly revolutionizing the field of urology, providing surgeons with powerful tools for a more complete understanding of patient-specific anatomy. Today, several new intraoperative imaging technologies and cutting-edge devices are available in adult urology to assist surgeons in delivering personalized interventions. Their applications are also gradually growing in general pediatric surgery, where the detailed visualization of normal and pathological structures has the potential to significantly minimize perioperative complications and improve surgical outcomes. In the field of pediatric urology, FGS, 3D reconstructions and printing technologies, augmented reality (AR) devices, contrast-enhanced ultrasound (CEUS), and intraoperative magnetic resonance imaging (iMRI) have been increasingly adopted for a more realistic understanding of the normal and abnormal anatomy, providing a valuable insight to deliver customized treatments in real time. This narrative review aims to illustrate the main applications of these new technologies and imaging devices in the clinical setting of pediatric urology by selecting, with a strict methodology, the most promising articles published in the international scientific literature on this topic. The purpose is to favor early adoption and stimulate more research on this topic for the benefit of children.
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Affiliation(s)
- Irene Paraboschi
- Department of Pediatric Urology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Guglielmo Mantica
- Department of Urology, Policlinico San Martino Hospital, University of Genoa, 16132 Genoa, Italy
| | - Dario Guido Minoli
- Department of Pediatric Urology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Erika Adalgisa De Marco
- Department of Pediatric Urology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Michele Gnech
- Department of Pediatric Urology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Carolina Bebi
- Department of Urology, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Università degli Studi di Milano, 20122 Milan, Italy
| | - Gianantonio Manzoni
- Department of Pediatric Urology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Alfredo Berrettini
- Department of Pediatric Urology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
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Surgical Management of Synchronous, Bilateral Renal Masses: A 1-decade Referral Center Experience. Eur Urol Focus 2022; 8:1309-1317. [PMID: 35123928 DOI: 10.1016/j.euf.2022.01.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/01/2021] [Accepted: 01/14/2022] [Indexed: 12/16/2022]
Abstract
BACKGROUND Management and decision-making in patients with bilateral renal masses are controversial. OBJECTIVE To report our experience of surgical management in patients with bilateral renal masses undergoing surgery at a high-volume center. DESIGN, SETTING, AND PARTICIPANTS We retrospectively collected data from patients treated with partial nephrectomy (PN) or radical nephrectomy for bilateral renal masses at a single referral institution between June 2008 and June 2019. Patient- and tumor-related features, timing (one vs two stage), and surgical approach (open vs robotic) were analyzed. SURGICAL PROCEDURE A one- versus two-stage strategy was adopted according to the opportunity to perform at least one PN using a clampless or selective-clamping approach, in order to avoid acute kidney injury. MEASUREMENTS Operative time, warm ischemia time, and intra- and postoperative complications were recorded. Histopathological results and tumor histology were assessed. RESULTS AND LIMITATIONS Overall, 41 patients were included. The median age was 67 yr and the median preoperative estimated glomerular filtration rate (eGFR) was 84 ml/min/1.73 m2. The median Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) score was 8 (interquartile range [IQR] 7-8) for both sides. In 17 (42%) patients, a simultaneous approach was chosen, with a pure robotic approach in 11/17 cases, while among the 24 (58.6%) patients treated with a two-stage strategy, 15 (62.5%) were treated with a robotic approach on both sides. Intraoperative complications and postoperative major (CDC ≥3) complications were recorded in 7.3% and 4.9% of cases, respectively. The overall positive surgical margins rate was 2.4%. At a median follow-up of 42 (IQR 18-59) mo, the median eGFR was 73 (IQR 64-80) ml/min/1.73 m2, while disease-free survival and cancer-specific mortality were 90.2% and 7.3%, respectively. CONCLUSIONS Our experience underlines that both simultaneous and staged surgical treatment of patients with bilateral renal masses are feasible and safe if grounded on proper patient selection. PATIENT SUMMARY Management of patients with bilateral renal masses is challenging, given the heterogeneity of clinical scenarios and the need to optimize the timing of treatment to achieve maximal functional preservation while ensuring oncological efficacy.
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Liu K, Zhao S, Li J, Zheng Y, Wu H, Kong J, Shen Z. Knowledge mapping and research hotspots of immunotherapy in renal cell carcinoma: A text-mining study from 2002 to 2021. Front Immunol 2022; 13:969217. [PMID: 35967367 PMCID: PMC9367473 DOI: 10.3389/fimmu.2022.969217] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 07/06/2022] [Indexed: 12/14/2022] Open
Abstract
Background Renal cell carcinoma (RCC) is one of the most lethal urological malignancies, and because early-stage RCC is asymptomatic, many patients present metastatic diseases at first diagnosis. With the development of immunotherapy, the treatment of RCC has entered a new stage and has made a series of progress. This study mainly outlines the knowledge map and detects the potential research hotspots by using bibliometric analysis. Methods Publications concerning RCC immunotherapy from 2002 to 2021 in the Web of Science Core Collection were collected. Visualization and statistical analysis were mainly performed by freeware tools VOSviewer, CiteSpace, R software, and Microsoft Office Excel 2019. Results A total of 3,432 papers were collected in this study, and the annual number of papers and citations showed a steady growth trend. The United States is the leading country with the most high-quality publications and is also the country with the most international cooperation. The University of Texas MD Anderson Cancer Center is the most productive organization. The Journal of Clinical Oncology is the highest co-cited journal, and Brian I. Rini is both the most prolific author and the author with the largest centrality. The current research hotspots may be focused on “immune checkpoint inhibitors (ICIs),” “PD-1,” and “mammalian target of rapamycin.” Conclusion Immunotherapy has a bright future in the field of RCC treatment, among which ICIs are one of the most important research hotspots. The main future research directions of ICI-based immunotherapy may focus on combination therapy, ICI monotherapy, and the development of new predictive biomarkers.
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Affiliation(s)
- Kun Liu
- Department of Urology, Xiamen Humanity Hospital, Fujian Medical University, Xiamen, China
| | - Seling Zhao
- Department of Urology, Xiamen Humanity Hospital, Fujian Medical University, Xiamen, China
| | - Jian Li
- Department of Urology, Xiamen Humanity Hospital, Fujian Medical University, Xiamen, China
| | - Yikun Zheng
- Department of Urology, Xiamen Humanity Hospital, Fujian Medical University, Xiamen, China
| | - Haiyang Wu
- Graduate School of Tianjin Medical University, Tianjin, China
- *Correspondence: Haiyang Wu, ; Jianqiu Kong, ; Zefeng Shen,
| | - Jianqiu Kong
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangzhou, China
- *Correspondence: Haiyang Wu, ; Jianqiu Kong, ; Zefeng Shen,
| | - Zefeng Shen
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- *Correspondence: Haiyang Wu, ; Jianqiu Kong, ; Zefeng Shen,
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AUTHOR REPLY. Urology 2022; 164:e316. [PMID: 35710185 DOI: 10.1016/j.urology.2021.10.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Corse T, Stifelman M, Yerram N. EDITORIAL COMMENT. Urology 2022; 164:e315. [PMID: 35710184 DOI: 10.1016/j.urology.2021.10.054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Artificial intelligence for renal cancer: From imaging to histology and beyond. Asian J Urol 2022; 9:243-252. [PMID: 36035341 PMCID: PMC9399557 DOI: 10.1016/j.ajur.2022.05.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 04/07/2022] [Accepted: 05/07/2022] [Indexed: 12/24/2022] Open
Abstract
Artificial intelligence (AI) has made considerable progress within the last decade and is the subject of contemporary literature. This trend is driven by improved computational abilities and increasing amounts of complex data that allow for new approaches in analysis and interpretation. Renal cell carcinoma (RCC) has a rising incidence since most tumors are now detected at an earlier stage due to improved imaging. This creates considerable challenges as approximately 10%–17% of kidney tumors are designated as benign in histopathological evaluation; however, certain co-morbid populations (the obese and elderly) have an increased peri-interventional risk. AI offers an alternative solution by helping to optimize precision and guidance for diagnostic and therapeutic decisions. The narrative review introduced basic principles and provide a comprehensive overview of current AI techniques for RCC. Currently, AI applications can be found in any aspect of RCC management including diagnostics, perioperative care, pathology, and follow-up. Most commonly applied models include neural networks, random forest, support vector machines, and regression. However, for implementation in daily practice, health care providers need to develop a basic understanding and establish interdisciplinary collaborations in order to standardize datasets, define meaningful endpoints, and unify interpretation.
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Amparore D, Pecoraro A, Piramide F, Verri P, Checcucci E, De Cillis S, Piana A, Burgio M, Di Dio M, Manfredi M, Fiori C, Porpiglia F. Three-dimensional imaging reconstruction of the kidney's anatomy for a tailored minimal invasive partial nephrectomy: A pilot study. Asian J Urol 2022; 9:263-271. [PMID: 36035345 PMCID: PMC9399544 DOI: 10.1016/j.ajur.2022.06.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Objective Methods Results Conclusion
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Affiliation(s)
- Daniele Amparore
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
- European Association of Urology (EAU) Young Academic Urologists (YAU) Renal Cancer Working Group, Arnhem, Netherlands
- Corresponding author. Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Angela Pecoraro
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
- European Association of Urology (EAU) Young Academic Urologists (YAU) Renal Cancer Working Group, Arnhem, Netherlands
| | - Federico Piramide
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Paolo Verri
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Enrico Checcucci
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
- European Association of Urology (EAU) Young Academic Urologists (YAU) Uro-technology and SoMe Working Group, Arnhem, Netherlands
| | - Sabrina De Cillis
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Alberto Piana
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Mariano Burgio
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Michele Di Dio
- Division of Urology, Department of Surgery, SS Annunziata Hospital, Cosenza, Italy
| | - Matteo Manfredi
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Cristian Fiori
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Francesco Porpiglia
- Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
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Puliatti S, Eissa A, Checcucci E, Piazza P, Amato M, Scarcella S, Rivas JG, Taratkin M, Marenco J, Rivero IB, Kowalewski KF, Cacciamani G, El-Sherbiny A, Zoeir A, El-Bahnasy AM, De Groote R, Mottrie A, Micali S. New imaging technologies for robotic kidney cancer surgery. Asian J Urol 2022; 9:253-262. [PMID: 36035346 PMCID: PMC9399539 DOI: 10.1016/j.ajur.2022.03.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 01/19/2022] [Accepted: 03/16/2022] [Indexed: 11/21/2022] Open
Abstract
Objective Kidney cancers account for approximately 2% of all newly diagnosed cancer in 2020. Among the primary treatment options for kidney cancer, urologist may choose between radical or partial nephrectomy, or ablative therapies. Nowadays, robotic-assisted partial nephrectomy (RAPN) for the management of renal cancers has gained popularity, up to being considered the gold standard. However, RAPN is a challenging procedure with a steep learning curve. Methods In this narrative review, different imaging technologies used to guide and aid RAPN are discussed. Results Three-dimensional visualization technology has been extensively discussed in RAPN, showing its value in enhancing robotic-surgery training, patient counseling, surgical planning, and intraoperative guidance. Intraoperative imaging technologies such as intracorporeal ultrasound, near-infrared fluorescent imaging, and intraoperative pathological examination can also be used to improve the outcomes following RAPN. Finally, artificial intelligence may play a role in the field of RAPN soon. Conclusion RAPN is a complex surgery; however, many imaging technologies may play an important role in facilitating it.
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Padovan E, Marullo G, Tanzi L, Piazzolla P, Moos S, Porpiglia F, Vezzetti E. A deep learning framework for real-time 3D model registration in robot-assisted laparoscopic surgery. Int J Med Robot 2022; 18:e2387. [PMID: 35246913 PMCID: PMC9286374 DOI: 10.1002/rcs.2387] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/31/2022] [Accepted: 03/03/2022] [Indexed: 12/18/2022]
Abstract
Introduction The current study presents a deep learning framework to determine, in real‐time, position and rotation of a target organ from an endoscopic video. These inferred data are used to overlay the 3D model of patient's organ over its real counterpart. The resulting augmented video flow is streamed back to the surgeon as a support during laparoscopic robot‐assisted procedures. Methods This framework exploits semantic segmentation and, thereafter, two techniques, based on Convolutional Neural Networks and motion analysis, were used to infer the rotation. Results The segmentation shows optimal accuracies, with a mean IoU score greater than 80% in all tests. Different performance levels are obtained for rotation, depending on the surgical procedure. Discussion Even if the presented methodology has various degrees of precision depending on the testing scenario, this work sets the first step for the adoption of deep learning and augmented reality to generalise the automatic registration process.
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Affiliation(s)
- Erica Padovan
- Department of Management, Production and Design Engineering, Polytechnic University of Turin, Turin, Italy
| | - Giorgia Marullo
- Department of Management, Production and Design Engineering, Polytechnic University of Turin, Turin, Italy
| | - Leonardo Tanzi
- Department of Management, Production and Design Engineering, Polytechnic University of Turin, Turin, Italy
| | - Pietro Piazzolla
- Department of Oncology, Division of Urology, School of Medicine, University of Turin, Turin, Italy
| | - Sandro Moos
- Department of Management, Production and Design Engineering, Polytechnic University of Turin, Turin, Italy
| | - Francesco Porpiglia
- Department of Oncology, Division of Urology, School of Medicine, University of Turin, Turin, Italy
| | - Enrico Vezzetti
- Department of Management, Production and Design Engineering, Polytechnic University of Turin, Turin, Italy
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Role and Utility of Mixed Reality Technology in Laparoscopic Partial Nephrectomy: Outcomes of a Prospective RCT Using an Indigenously Developed Software. Adv Urol 2022; 2022:8992051. [PMID: 35615077 PMCID: PMC9126718 DOI: 10.1155/2022/8992051] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 04/07/2022] [Accepted: 04/23/2022] [Indexed: 11/17/2022] Open
Abstract
Objective To develop a software for mixed reality (MR) anatomical model creation and study its intraoperative clinical utility to facilitate laparoscopic partial nephrectomy. Materials and Methods After institutional review board approval, 47 patients were prospectively randomized for LPN into two groups: the control group (24 patients) underwent operation with an intraoperative ultrasound (US) control and the experimental group (23 patients) with smart glasses HoloLens 2 (Microsoft, Seattle, WA, USA). Our team has developed an open-source software package called “HLOIA,” utilization of which allowed to create and use during surgery the MR anatomical model of the kidney with its vascular pedicle and tumor. The study period extended from June 2020 to February 2021 where demographic, perioperative, and pathological data were collected for all qualifying patients. The objective was to assess the utility of a MR model during LPN and through a 5-point Likert scale questionnaire, completed by the surgeon, immediately after LPN. Patient characteristics were tested using the chi-square test for categorical variables and Student's t-test or Mann–Whitney test for continuous variables. Results Comparison of the variables between the groups revealed statistically significant differences only in the following parameters: the time for renal pedicle exposure and the time from the renal pedicle to the detection of tumor localization (p < 0.001), which were in favor of the experimental group. The surgeon's impression of the utility of the MR model by the proposed questionnaire demonstrated high scores in all statements. Conclusions Developed open-source software “HLOIA” allowed to create the mixed reality anatomical model by operating urologist which is when used with smart glasses has shown improvement in terms of time for renal pedicle exposure and time for renal tumor identification without compromising safety.
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Fiori C, Porpiglia F. Renal cancer: From current evidences to future perspectives. Asian J Urol 2022; 9:199-200. [PMID: 36035348 PMCID: PMC9399550 DOI: 10.1016/j.ajur.2022.05.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 05/18/2022] [Indexed: 11/29/2022] Open
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Roberts S, Desai A, Checcucci E, Puliatti S, Taratkin M, Kowalewski KF, Gomez Rivas J, Rivero I, Veneziano D, Autorino R, Porpiglia F, Gill IS, Cacciamani GE. "Augmented reality" applications in urology: a systematic review. Minerva Urol Nephrol 2022; 74:528-537. [PMID: 35383432 DOI: 10.23736/s2724-6051.22.04726-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
INTRODUCTION Augmented reality (AR) applied to surgical procedures refers to the superimposition of preoperative or intra-operative images onto the operative field. Augmented reality has been increasingly used in myriad surgical specialties including Urology. The following study reviews advances in the use of AR for improvements in urologic outcomes. EVIDENCE ACQUISITION We identified all descriptive, validity, prospective randomized/nonrandomized trials and retrospective comparative/noncomparative studies about the use of AR in Urology up until March 2021. The MEDLINE, Scopus, and Web of Science databases were used for literature search. We conducted the study selection according to the PRISMA (Preferred Reporting Items for Systematic Reviews and meta-analysis statement) guidelines. We limited included studies to only those using AR, excluding all that used virtual reality technology. EVIDENCE SYNTHESIS A total of 60 studies were identified and included in the present analysis. Overall, 19 studies were descriptive/validity/phantom studies for specific AR methodologies, 4 studies were case reports, and 37 studies included clinical prospective/retrospective comparative studies. CONCLUSIONS Advances in AR have led to increasing registration accuracy as well as increased ability to identify anatomic landmarks and improve outcomes during Urologic procedures such as RARP and robot-assisted partial nephrectomy.
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Affiliation(s)
- Sidney Roberts
- Keck School of Medicine, Catherine and Joseph Aresty Department of Urology, USC Institute of Urology, Los Angeles, CA, USA
| | - Aditya Desai
- Keck School of Medicine, Catherine and Joseph Aresty Department of Urology, USC Institute of Urology, Los Angeles, CA, USA
| | - Enrico Checcucci
- School of Medicine, Division of Urology, Department of Oncology, San Luigi Hospital, University of Turin, Orbassano, Turin, Italy.,European Association of Urology (EAU) Young Academic Office (YAU) Uro-Technology Working Group, Arnhem, the Netherlands
| | - Stefano Puliatti
- European Association of Urology (EAU) Young Academic Office (YAU) Uro-Technology Working Group, Arnhem, the Netherlands.,Department of Urology, University of Modena and Reggio Emilia, Modena, Italy.,Department of Urology, OLV, Aalst, Belgium.,ORSI Academy, Melle, Belgium
| | - Mark Taratkin
- European Association of Urology (EAU) Young Academic Office (YAU) Uro-Technology Working Group, Arnhem, the Netherlands.,Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia
| | - Karl-Friedrich Kowalewski
- European Association of Urology (EAU) Young Academic Office (YAU) Uro-Technology Working Group, Arnhem, the Netherlands.,Virgen Macarena University Hospital, Seville, Spain.,Department of Urology and Urosurgery, University Hospital of Mannheim, Mannheim, Germany
| | - Juan Gomez Rivas
- European Association of Urology (EAU) Young Academic Office (YAU) Uro-Technology Working Group, Arnhem, the Netherlands.,Department of Urology, Clinico San Carlos University Hospital, Madrid, Spain
| | - Ines Rivero
- European Association of Urology (EAU) Young Academic Office (YAU) Uro-Technology Working Group, Arnhem, the Netherlands.,Department of Urology and Nephrology, Virgen del Rocío University Hospital, Seville, Spain
| | - Domenico Veneziano
- European Association of Urology (EAU) Young Academic Office (YAU) Uro-Technology Working Group, Arnhem, the Netherlands.,Department of Urology, Riuniti Hospital, Reggio Calabria, Reggio Calabria, Italy
| | | | - Francesco Porpiglia
- European Association of Urology (EAU) Young Academic Office (YAU) Uro-Technology Working Group, Arnhem, the Netherlands
| | - Inderbir S Gill
- Keck School of Medicine, Catherine and Joseph Aresty Department of Urology, USC Institute of Urology, Los Angeles, CA, USA.,Artificial Intelligence (AI) Center at USC Urology, USC Institute of Urology, Los Angeles, CA, USA
| | - Giovanni E Cacciamani
- Keck School of Medicine, Catherine and Joseph Aresty Department of Urology, USC Institute of Urology, Los Angeles, CA, USA - .,European Association of Urology (EAU) Young Academic Office (YAU) Uro-Technology Working Group, Arnhem, the Netherlands.,Artificial Intelligence (AI) Center at USC Urology, USC Institute of Urology, Los Angeles, CA, USA.,Keck School of Medicine, Department of Radiology, University of Southern California, Los Angeles, CA, USA
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